Off the Shelf Datasets
Our licensable datasets to jumpstart your AI projects
Product Catalog
While open data or public data sets are convenient, we offer an extensive catalog of ‘off-the-shelf’, 250+ licensable datasets across 80 languages across multiple dialects for a variety of common AI use cases. We are excited to announce 30+ new datasets for 2020 that deliver immediate value to our customers. Among our offerings, you will find data sets for speech recognition, learning datasets for machine learning algorithms, all created with the most advanced available data science.
Speed
Available immediately to support your AI/ML projects today
Cost Effective
Licensed data sets are more economical than custom data collection
Expertise
20+ years’ data collection experience
Support All Data Types
Image, video, speech, audio, and text
Scale
Provide the right amount of data to train your models effectively
Quality
Improve quality and minimize bias in your AI models
| Dataset Name | Product Type | Common Use Cases | Recording Device | Unit |
|---|
| Dataset Name | Product Type | Common Use Cases | Recording Device | Unit | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 138 |   Albanian (Albania) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 12,000 words | Add Quote | sqi_ALB_PHON | Appen Global | Pronunciation Dictionary | Albanian | Albania | N/A | N/A | N/A | N/A | 12,000 | N/A | text | Albanian (Albania) Pronunciation Dictionary | |
| 139 | Amharic (Ethiopia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 45,000 words | Add Quote | amh_ETH_PHON | Appen Global | Pronunciation Dictionary | Amharic | Ethiopia | N/A | N/A | N/A | N/A | 45,000 | N/A | text | Amharic (Ethiopia) Pronunciation Dictionary | |
| 144 | Arabic (Algeria) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 11,000 words | Add Quote | ara_DZA_PHON | Appen Global | Pronunciation Dictionary | Arabic | Algeria | N/A | N/A | N/A | N/A | 11,000 | N/A | text | Arabic (Algeria) Pronunciation Dictionary | |
| 20 |  Arabic (Eastern Algeria) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 29 hours | Add Quote | EAR_ASR001 | Appen Global | Conversational Speech | Arabic | Algeria | Low background noise (home/office) | 496 | 2 | Available on request | 11,327 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words For the majority of calls, both speakers (in-line/out-line) were collected and transcribed however, for a smaller number of calls, only one half of the conversation was collected and transcribed | Arabic (Eastern Algeria) conversational telephony |
| 140 | Arabic (Egypt) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 40,000 words | Add Quote | ara_EGY_PHON | Appen Global | Pronunciation Dictionary | Arabic | Egypt | N/A | N/A | N/A | N/A | 40,000 | N/A | text | Arabic (Egypt) Pronunciation Dictionary | |
| 114 | Arabic (Egypt) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 352 hours | Add Quote | ARE_ASR001_CN | Appen China | Scripted Speech | Arabic | Egypt | Low background noise (home/office) | 627 | 1 | 128,908 | 207,576 | 16 | wav | Dataset is fully transcribed | Arabic (Egypt) scripted smartphone |
| 142 | Arabic (Iraq) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 13,000 words | Add Quote | ara_IRQ_POS | Appen Global | Part of Speech Dictionary | Arabic | Iraq | N/A | N/A | N/A | N/A | 13,000 | N/A | text | Arabic (Iraq) Part of Speech Dictionary | |
| 141 | Arabic (Iraq) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | ara_IRQ_PHON | Appen Global | Pronunciation Dictionary | Arabic | Iraq | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Person names | Arabic (Iraq) Pronunciation Dictionary |
| 143 | Arabic (Libya) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 48,000 words | Add Quote | ara_LBY_PHON | Appen Global | Pronunciation Dictionary | Arabic | Libya | N/A | N/A | N/A | N/A | 48,000 | N/A | text | Arabic (Libya) Pronunciation Dictionary | |
| 65 | Arabic (Modern Standard Arabic) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 12 hours | Add Quote | MSA_ASR001 | Global Phone | Scripted Speech | Arabic | Tunisia | Low background noise (home/office) | 78 | 1 | 4,908 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Arabic (Modern Standard Arabic) scripted microphone |
| 112 | Arabic (Morocco) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 33 hours | Add Quote | ARY_ASR001 | Appen Global | Conversational Speech | Arabic | Morocco | Low background noise | 180 | 2 | 80,544 | 23,836 | 8 | alaw | Each speaker participated in 1 to 4 conversations. Speakers are identified by a unique 4-digit speaker ID which is recorded in the demographic file Transcription is available in original script and fully reversible Romanised version with accompanying pronunciation lexicon English translation of product transcription is available (ARY_MT001, ARY_ASRMT001) | Arabic (Morocco) conversational telephony |
| 113 | Arabic (Morocco) conversational telephony translation | Text | MT, Chatbot , Conversational AI | N/A | 80,544 utterances | Add Quote | ARY_MT001 | Appen Global | Conversational Translation | Arabic | Morocco | N/A | 180 | N/A | 80,430 | 23,844 | N/A | text | Corresponding audio, transcription, fully reversible romanised transcription and pronunciation lexicon data are available (ARY_ASR001, ARY_ASRMT001) | Arabic (Morocco) conversational telephony translation |
| 146 | Arabic (Morocco) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 60,000 words | Add Quote | ara_MAR_PHON | Appen Global | Pronunciation Dictionary | Arabic | Morocco | N/A | N/A | N/A | N/A | 60,000 | N/A | text | Arabic (Morocco) Pronunciation Dictionary | |
| 147 | Arabic (N/A) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 40,000 words | Add Quote | arb_N/A_PHON | Appen Global | Pronunciation Dictionary | Arabic | N/A | N/A | N/A | N/A | N/A | 40,000 | N/A | text | Arabic (N/A) Pronunciation Dictionary | |
| 115 | Arabic (Saudi Arabia) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 322 hours | Add Quote | ARS_ASR001_CN | Appen China | Scripted Speech | Arabic | Saudi Arabia | Low background noise (home/office) | 227 | 1 | 104,574 | 156,282 | 16 | wav | Dataset is fully transcribed | Arabic (Saudi Arabia) scripted smartphone |
| 149 | Arabic (Sudan) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 17,000 words | Add Quote | ara_SDN_PHON | Appen Global | Pronunciation Dictionary | Arabic | Sudan | N/A | N/A | N/A | N/A | 17,000 | N/A | text | Arabic (Sudan) Pronunciation Dictionary | |
| 148 | Arabic (United Arab Emirates) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 75,000 words | Add Quote | ara_ARE_PHON | Appen Global | Pronunciation Dictionary | Arabic | United Arab Emirates | N/A | N/A | N/A | N/A | 75,000 | N/A | text | Arabic (United Arab Emirates) Pronunciation Dictionary | |
| 122 | Arabic (United Arab Emirates) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 170 hours | Add Quote | ARU_ASR001_CN | Appen China | Scripted Speech | Arabic | United Arab Emirates | Low background noise (home/office) | 133 | 1 | 42,352 | 85,775 | 16 | wav | Dataset is fully transcribed | Arabic (United Arab Emirates) scripted smartphone |
| 70 | Arabic (United Arab Emirates) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 48 hours | Add Quote | OrienTel United Arab Emirates MCA (Modern Colloquial Arabic) | Nuance | Scripted Speech | Arabic | United Arab Emirates | Low background noise | 880 | 1 | 43,000 | Available on request | 8 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 49 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words and spontaneous items for control | Arabic (United Arab Emirates) scripted telephony |
| 71 | Arabic (United Arab Emirates) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 31 hours | Add Quote | OrienTel United Arab Emirates MSA (Modern Standard Arabic) | Nuance | Scripted Speech | Arabic | United Arab Emirates | Low background noise | 500 | 1 | 24,500 | Available on request | 8 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 49 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words and spontaneous items for control | Arabic (United Arab Emirates) scripted telephony |
| 9 | Arabic (United Arab Emirates/ Saudi Arabia) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 86 hours | Add Quote | CGA_ASR001 | Appen Global | Scripted Speech | Arabic | United Arab Emirates; Saudi Arabia | Low background noise (home/office) | 150 | 4 | 42,000 | 19,245 | 16 | alaw | Complete transcriptions of the content of the speech files at a word level All acoustic events have been tagged using conventions derived from the SpeechDATmodel All transcriptions fully vowelized 280 prompts per speaker including 30 Person names (first name and family name) from a set of 15, 10 single isolated digits 0-10, 8-digit sequences (randomly generated), 200 phonetically balanced sentences, 30 x 10-word phonetically balanced word strings | Arabic (United Arab Emirates/ Saudi Arabia) scripted microphone |
| 130 | Arabic NER news text | Text | NER, Content Classification, Search Engines | N/A | 20,774 sentences | Add Quote | ARB_NER001 | Appen Global | News NER | Standard Arabic | N/A | N/A | N/A | N/A | 20,774 | Available on request | N/A | text | Arabic NER news text | |
| 150 | Assamese (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 40,000 words | Add Quote | asm_IND_PHON | Appen Global | Pronunciation Dictionary | Assamese | India | N/A | N/A | N/A | N/A | 40,000 | N/A | text | Assamese (India) Pronunciation Dictionary | |
| 124 | Baby crying audio | Audio | Baby Monitor, Security & Other Consumer Applications | Mobile phone | 3 hours | Add Quote | CRY_ASR001 | Appen China | Human Sound | N/A | China | Low background noise (home/office) | 100 | 1 | NA | NA | 16 | wav | Crying sound of babies 0-3 years old, each lasting around 2 minutes. | Baby crying audio |
| 4 | Bahasa Indonesia conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 31 hours | Add Quote | BAH_ASR001 | Appen Global | Conversational Speech | Indonesian | Indonesia | Low background noise | 1,002 | 2 | Available on request | 11,480 | 8 | wav | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words For a large proportion of calls, only one half of the conversation was collected and transcribed | Bahasa Indonesia conversational telephony |
| 153 | Basque (Spain) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 10,000 words | Add Quote | eus_ESP_PHON | Appen Global | Pronunciation Dictionary | Basque | Spain | N/A | N/A | N/A | N/A | 10,000 | N/A | text | Basque (Spain) Pronunciation Dictionary | |
| 6 | Bengali (Bangladesh) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 47 hours | Add Quote | BEN_ASR001 | Appen Global | Conversational Speech | Bengali | Bangladesh | Mixed (in-car, roadside, home/office) | 1,000 | 2 | Available on request | 17,922 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words | Bengali (Bangladesh) conversational telephony |
| 154 | Bengali (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 29,000 words | Add Quote | ben_IND_PHON | Appen Global | Pronunciation Dictionary | Bengali | India | N/A | N/A | N/A | N/A | 29,000 | N/A | text | Bengali (India) Pronunciation Dictionary | |
| 7 | Bulgarian (Bulgaria) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 38 hours | Add Quote | BUL_ASR001 | Appen Global | Conversational Speech | Bulgarian | Bulgaria | Low background noise (home/office) | 217 | 2 | Available on request | 22,342 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Bulgarian (Bulgaria) conversational telephony |
| 155 | Bulgarian (Bulgaria) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 55,000 words | Add Quote | bul_BGR_PHON | Appen Global | Pronunciation Dictionary | Bulgarian | Bulgaria | N/A | N/A | N/A | N/A | 55,000 | N/A | text | Bulgarian (Bulgaria) Pronunciation Dictionary | |
| 111 | Bulgarian (Bulgaria) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 22 hours | Add Quote | BUL_ASR002 | Global Phone | Scripted Speech | Bulgarian | Bulgaria | Low background noise (home/office) | 77 | 1 | 8,674 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Bulgarian (Bulgaria) scripted microphone |
| 158 | Cantonese (China) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 10,000 words | Add Quote | yue_HKG_POS | Appen Global | Part of Speech Dictionary | Cantonese | China | N/A | N/A | N/A | N/A | 10,000 | N/A | text | Traditional | Cantonese (China) Part of Speech Dictionary |
| 156 | Cantonese (China) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 37,000 words | Add Quote | yue_CHN_PHON | Appen Global | Pronunciation Dictionary | Cantonese | China | N/A | N/A | N/A | N/A | 37,000 | N/A | text | Simplified | Cantonese (China) Pronunciation Dictionary |
| 157 | Cantonese (China) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 40,000 words | Add Quote | yue_CHN_PHON | Appen Global | Pronunciation Dictionary | Cantonese | China | N/A | N/A | N/A | N/A | 40,000 | N/A | text | Traditional | Cantonese (China) Pronunciation Dictionary |
| 159 | Catalan (Spain) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 10,000 words | Add Quote | cat_ESP_PHON | Appen Global | Pronunciation Dictionary | Catalan | Spain | N/A | N/A | N/A | N/A | 10,000 | N/A | text | Catalan (Spain) Pronunciation Dictionary | |
| 160 | Cebuano (Philippines) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 20,000 words | Add Quote | ceb_PHL_PHON | Appen Global | Pronunciation Dictionary | Cebuano | Philippines | N/A | N/A | N/A | N/A | 20,000 | N/A | text | Cebuano (Philippines) Pronunciation Dictionary | |
| 10 | Croatian (Croatia) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 39 hours | Add Quote | CRO_ASR001 | Appen Global | Conversational Speech | Croatian | Croatia | Low background noise (home/office) | 200 | 2 | Available on request | 23,919 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Croatian (Croatia) conversational telephony |
| 161 | Croatian (Croatia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 20,000 words | Add Quote | hrv_HRV_PHON | Appen Global | Pronunciation Dictionary | Croatian | Croatia | N/A | N/A | N/A | N/A | 20,000 | N/A | text | Croatian (Croatia) Pronunciation Dictionary | |
| 11 | Croatian (Croatia) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 11 hours | Add Quote | CRO_ASR002 | Global Phone | Scripted Speech | Croatian | Croatia | Low background noise (home/office) | 94 | 1 | 4,499 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Croatian (Croatia) scripted microphone |
| 116 | Croatian (Croatia) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 263 hours | Add Quote | CRO_ASR003_CN | Appen China | Scripted Speech | Croatian | Croatia | Low background noise (home/office) | 243 | 1 | 73,467 | 136,140 | 16 | wav | Dataset is fully transcribed | Croatian (Croatia) scripted smartphone |
| 162 | Czech (Czech Republic) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 50,000 words | Add Quote | ces_CZE_PHON | Appen Global | Pronunciation Dictionary | Czech | Czech Republic | N/A | N/A | N/A | N/A | 50,000 | N/A | text | Czech (Czech Republic) Pronunciation Dictionary | |
| 12 | Czech (Czech Republic) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 31 hours | Add Quote | CZE_ASR001 | Global Phone | Scripted Speech | Czech | Czech Republic | Low background noise (home/office) | 102 | 1 | 12,425 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Czech (Czech Republic) scripted microphone |
| 13 | Czech (Czech Republic) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 93 hours | Add Quote | Czech SpeechDat(E) Dataset | Nuance | Scripted Speech | Czech | Czech Republic | Low background noise | 1,000 | 1 | 52,000 | Available on request | 8 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 52 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items, and phonetically rich words and sentences | Czech (Czech Republic) scripted telephony |
| 164 | Danish (Denmark) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 100,000 words | Add Quote | dan_DNK_POS | Appen Global | Part of Speech Dictionary | Danish | Denmark | N/A | N/A | N/A | N/A | 100,000 | N/A | text | Danish (Denmark) Part of Speech Dictionary | |
| 163 | Danish (Denmark) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 107,000 words | Add Quote | dan_DNK_PHON | Appen Global | Pronunciation Dictionary | Danish | Denmark | N/A | N/A | N/A | N/A | 107,000 | N/A | text | Danish (Denmark) Pronunciation Dictionary | |
| 90 | Danish (Denmark) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 53 hours | Add Quote | Speecon Danish | Nuance | Scripted Speech | Danish | Denmark | Mixed (office, entertainment, car, public place) | 600 (550 adult speakers and 50 child speakers) | 4 | 170,000 | Available on request | 16 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 290 prompts per adult speaker and 210 prompts per child speaker including digits, natural numbers, letter strings, personal, place and business names, application words for adult speakers, command (toy, phone and general) for child speakers, phonetically rich words and sentences and free and elicited spontaneous responses for adult speakers | Danish (Denmark) scripted microphone |
| 15 | Dari (Afghanistan) broadcast data | Audio | ASR, Automatic Captioning, Keyword Spotting | Microphone | 51 hours | Add Quote | DAR_BRC001 | Appen Global | Broadcast Speech | Dari | Afghanistan | Low background noise (studio) | N/A | 1 | Available on request | Available on request | N/A | wav | Dataset is fully transcribed and timestamped Dataset is largely speech only and does not include music or advertisements Data types include: talk shows, interviews, news broadcasts (excluding news reading by anchors) | Dari (Afghanistan) broadcast data |
| 14 | Dari (Afghanistan) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 40 hours | Add Quote | DAR_ASR001 | Appen Global | Conversational Speech | Dari | Afghanistan | Low background noise | 500 | 2 | Available on request | 11,168 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is largely speech only and does not include music or advertisements | Dari (Afghanistan) conversational telephony |
| 165 | Dari (Afghanistan) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 30,000 words | Add Quote | prs_AFG_PHON | Appen Global | Pronunciation Dictionary | Dari | Afghanistan | N/A | N/A | N/A | N/A | 30,000 | N/A | text | Dari (Afghanistan) Pronunciation Dictionary | |
| 166 | Dholuo (Kenya) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 20,000 words | Add Quote | luo_KEN_PHON | Appen Global | Pronunciation Dictionary | Dholuo | Kenya | N/A | N/A | N/A | N/A | 20,000 | N/A | text | Dholuo (Kenya) Pronunciation Dictionary | |
| 91 | Dutch (Belgium) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 47 hours | Add Quote | Speecon Dutch from Belgium | Nuance | Scripted Speech | Dutch | Belgium | Mixed (office, entertainment, car, public place) | 600 (550 adult speakers and 50 child speakers) | 4 | 170,000 | Available on request | 16 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 290 prompts per adult speaker and 210 prompts per child speaker including digits, natural numbers, letter strings, personal, place and business names, application words for adult speakers, command (toy, phone and general) for child speakers, phonetically rich words and sentences and free and elicited spontaneous responses for adult speakers | Dutch (Belgium) scripted microphone |
| 33 | Dutch (Belgium) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Microphone | 80 hours | Add Quote | Flemish SpeechDat(II) FDB-1000 (FIXED1FL) | Nuance | Scripted Speech | Dutch | Belgium | Low background noise | 1,000 | 1 | 52,000 | Available on request | 8 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 52 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words and spontaneous items for control | Dutch (Belgium) scripted telephony |
| 19 | Dutch (Netherlands & Belgium) scripted in-car | Audio | ASR, Virtual Assistant, In Car HMI & Entertainment | Microphone and mobile phone | 27 hours | Add Quote | Dutch and Flemish SpeechDat-Car | Nuance | Scripted Speech | Dutch | Netherland; Belgium | Mixed (in-car) | 302 | 5 | 15,100 | Available on request | 16 and 8 | alaw | Dataset is fully transcribed and is accompanied by a pronunciation lexicon and validation report 125 prompts per adult speaker including digits, natural numbers, letter strings, personal, place and business names (some spontaneous), generic command and control items, phonetically rich words and sentences and prompts for spontaneous speech | Dutch (Netherlands & Belgium) scripted in-car |
| 66 | Dutch (Netherlands) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 36 hours | Add Quote | NLD_ASR001 | Appen Global | Conversational Speech | Dutch | Netherlands | Low background noise | 200 | 2 | Available on request | 14,964 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Dutch (Netherlands) conversational telephony |
| 167 | Dutch (Netherlands) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 45,000 words | Add Quote | nld_NLD_PHON | Appen Global | Pronunciation Dictionary | Dutch | Netherlands | N/A | N/A | N/A | N/A | 45,000 | N/A | text | Dutch (Netherlands) Pronunciation Dictionary | |
| 92 | Dutch (Netherlands) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 68 hours | Add Quote | Speecon Dutch from the Netherlands | Nuance | Scripted Speech | Dutch | Netherlands | Mixed (office, entertainment, car, public place) | 600 (550 adult speakers and 50 child speakers) | 4 | 170,000 | Available on request | 16 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 290 prompts per adult speaker and 210 prompts per child speaker including digits, natural numbers, letter strings, personal, place and business names, application words for adult speakers, command (toy, phone and general) for child speakers, phonetically rich words and sentences and free and elicited spontaneous responses for adult speakers | Dutch (Netherlands) scripted microphone |
| 125 |  East African facial images | Image | Facial Recognition | Camera | 13500 images | Add Quote | IMG_FACE_KEN_CN | Appen China | Human Face | N/A | Kenya | Mixed background and lighting conditions | 100 | NA | NA | NA | NA | jpg | East African facial images | |
| 21 | English (Arabic - Levant/Egypt) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 28 hours | Add Quote | ENA_ASR001 | Appen Global | Conversational Speech | English | Egypt | Low background noise | 250 | 2 | Available on request | 5,619 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words Average length of calls: 10-15 mins | English (Arabic - Levant/Egypt) conversational telephony |
| 169 | English (Australia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 157,000 words | Add Quote | eng_AUS_PHON | Appen Global | Pronunciation Dictionary | English | Australia | N/A | N/A | N/A | N/A | 157,000 | N/A | text | English (Australia) Pronunciation Dictionary | |
| 2 | English (Australia) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 92 hours | Add Quote | AUS_ASR001 | Appen Global | Scripted Speech | English | Australia | Low background noise (home/office) | 500 | 1 | 82,500 | 35,137 | 8 | alaw | Fully transcribed to SpeechDAT type conventions Dataset is accompanied by a pronunciation lexicon containing all transcribed words 162 prompts (read speech) per speaker including digits, natural numbers, letter strings, personal, place, and business names, confirmation items (yes, no + fuzzy), generic command and control items (from a set of 215), phonetically rich sentences and words | English (Australia) scripted telephony |
| 3 | English (Australia) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 118 hours | Add Quote | AUS_ASR002 | Appen Global | Scripted Speech | English | Australia | Mixed | 1,000 | 1 | 75,000 | 19 | 8 | alaw | Fully transcribed to SpeechDAT type conventions Dataset is accompanied by a pronunciation lexicon containing all transcribed words 75 prompts per speaker including digits, natural numbers, letter strings, personal, place, and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words The prompts are a mixture of 'read' and 'elicited' items where 5 prompts per script are 'spontaneous free speech' | English (Australia) scripted telephony |
| 171 | English (Canada) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 3,000 words | Add Quote | eng_CAN_POS | Appen Global | Part of Speech Dictionary | English | Canada | N/A | N/A | N/A | N/A | 3,000 | N/A | text | English (Canada) Part of Speech Dictionary | |
| 170 | English (Canada) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 50,000 words | Add Quote | eng_CAN_PHON | Appen Global | Pronunciation Dictionary | English | Canada | N/A | N/A | N/A | N/A | 50,000 | N/A | text | English (Canada) Pronunciation Dictionary | |
| 22 | English (Canada) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 144 hours | Add Quote | ENC_ASR001 | Appen Global | Scripted Speech | English | Canada | Mixed | 1,000 | 1 | 99,000 | 12,483 | 8 | alaw or wav | Fully transcribed to SALA II/SpeechDAT type conventions Dataset is accompanied by a pronunciation lexicon containing all transcribed words 99 prompts per speaker including digits, natural numbers, letter strings, personal, place, and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words | English (Canada) scripted telephony |
| 173 | English (Hong Kong) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 18,000 words | Add Quote | eng_HKG_PHON | Appen Global | Pronunciation Dictionary | English | Hong Kong | N/A | N/A | N/A | N/A | 18,000 | N/A | text | English (Hong Kong) Pronunciation Dictionary | |
| 25 | English (India) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 67 hours | Add Quote | ENI_ASR002 | Appen Global | Conversational Speech | English | India | Low background noise | 540 | 2 | 77,565 | 11,646 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 271 telephony conversations are recorded for this project | English (India) conversational telephony |
| 175 | English (India) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 13,000 words | Add Quote | eng_IND_POS | Appen Global | Part of Speech Dictionary | English | India | N/A | N/A | N/A | N/A | 13,000 | N/A | text | English (India) Part of Speech Dictionary | |
| 174 | English (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 60,000 words | Add Quote | eng_IND_PHON | Appen Global | Pronunciation Dictionary | English | India | N/A | N/A | N/A | N/A | 60,000 | N/A | text | English (India) Pronunciation Dictionary | |
| 24 | English (India) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 217 hours | Add Quote | ENI_ASR001 | Appen Global | Scripted Speech | English | India | Mixed | 2,358 | 1 | 117,900 | 9,190 | 8 | alaw | Fully transcribed to SpeechDAT type conventions. Dataset is accompanied by a pronunciation lexicon [SAMPA] containing all transcribed words 49 prompts per speaker including digits, natural numbers, letter strings, personal, place, and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words | English (India) scripted telephony |
| 176 | English (Ireland) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 12,000 words | Add Quote | eng_IRL_PHON | Appen Global | Pronunciation Dictionary | English | Ireland | N/A | N/A | N/A | N/A | 12,000 | N/A | text | English (Ireland) Pronunciation Dictionary | |
| 177 | English (NZ) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 50,000 words | Add Quote | eng_NZL_PHON | Appen Global | Pronunciation Dictionary | English | NZ | N/A | N/A | N/A | N/A | 50,000 | N/A | text | English (NZ) Pronunciation Dictionary | |
| 23 | English (Philippines) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 53 hours | Add Quote | ENF_ASR001 | Appen Global | Conversational Speech | English | Philippines | Low background noise | 450 | 2 | 41,602 | 7,272 | 8 | alaw or wav | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words Average length of calls: 10-15 mins | English (Philippines) conversational telephony |
| 172 | English (Philippines) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 5,000 words | Add Quote | eng_PHL_PHON | Appen Global | Pronunciation Dictionary | English | Philippines | N/A | N/A | N/A | N/A | 5,000 | N/A | text | English (Philippines) Pronunciation Dictionary | |
| 168 | English (United Arab Emirates) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 5,000 words | Add Quote | eng_ARE_PHON | Appen Global | Pronunciation Dictionary | English | United Arab Emirates | N/A | N/A | N/A | N/A | 5,000 | N/A | text | English (United Arab Emirates) Pronunciation Dictionary | |
| 67 | English (United Arab Emirates) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 33 hours | Add Quote | OrienTel English as spoken in the United Arab Emirates | Nuance | Scripted Speech | English | United Arab Emirates | Low background noise | 500 | 1 | 25,500 | Available on request | 8 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 51 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words and spontaneous items for control | English (United Arab Emirates) scripted telephony |
| 99 | English (United Kingdom) | Audio | TTS | Headset microphone | 10 hours | Add Quote | TC-STAR female baseline voice Laura | Nuance | Scripted Speech | English | United Kingdom | Low background noise (studio) | 1 | 1 | Available on request | Available on request | 96 | Available on request | Dataset includes manual orthographic transcription, automatic segmentation into phonemes, automatic generation of pitch marks (where a certain percentage of phonetic segments and pitch marks has been manually checked) Dataset is accompanied by a pronunciation lexicon with POS, lemma and phonetic transcription | English (United Kingdom) |
| 100 | English (United Kingdom) | Audio | TTS | Headset microphone | 10 hours | Add Quote | TC-STAR male baseline voice Ian | Nuance | Scripted Speech | English | United Kingdom | Low background noise (studio) | 1 | 1 | Available on request | Available on request | 96 | Available on request | Dataset includes manual orthographic transcription, automatic segmentation into phonemes, automatic generation of pitch marks (where a certain percentage of phonetic segments and pitch marks has been manually checked) Dataset is accompanied by a pronunciation lexicon with POS, lemma and phonetic transcription | English (United Kingdom) |
| 259 | English (United Kingdom) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 50 hours | Add Quote | UKE_ASR001B | Appen Global | Conversational Speech | English | United Kingdom | Low background noise | 1,150 | 2 | Available on request | 13,192 | 8 | wav | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words | English (United Kingdom) conversational telephony |
| 104 | English (United Kingdom) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 150 hours | Add Quote | UKE_ASR001 | Appen Global | Conversational Speech | English | United Kingdom | Low background noise | 1,150 | 2 | 298,562 | 24,193 | 8 | wav | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words | English (United Kingdom) conversational telephony |
| 179 | English (United Kingdom) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 155,000 words | Add Quote | eng_GBR_POS | Appen Global | Part of Speech Dictionary | English | United Kingdom | N/A | N/A | N/A | N/A | 155,000 | N/A | text | English (United Kingdom) Part of Speech Dictionary | |
| 178 | English (United Kingdom) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 195,000 words | Add Quote | eng_GBR_PHON | Appen Global | Pronunciation Dictionary | English | United Kingdom | N/A | N/A | N/A | N/A | 195,000 | N/A | text | English (United Kingdom) Pronunciation Dictionary | |
| 107 | English (United States) conversational smartphone | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone | 1000 hours | Add Quote | USE_ASR003 | Appen Global | Conversational Speech | English | United States | Low background noise | 2,000 | 1 | 500,000 | 52,586 | 16 | wav | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words Conversations cover a wide variety of topics including: study/major/work, hometown, living arrangements, weather and seasons, punctuality, TV programs/film) | English (United States) conversational smartphone |
| 181 | English (United States) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 263,000 words | Add Quote | eng_USA_POS | Appen Global | Part of Speech Dictionary | English | United States | N/A | N/A | N/A | N/A | 263,000 | N/A | text | English (United States) Part of Speech Dictionary | |
| 180 | English (United States) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 330,000 words | Add Quote | eng_USA_PHON | Appen Global | Pronunciation Dictionary | English | United States | N/A | N/A | N/A | N/A | 330,000 | N/A | text | English (United States) Pronunciation Dictionary | |
| 93 | English (United States) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 53 hours | Add Quote | Speecon English (USA) database | Nuance | Scripted Speech | English | United States | Mixed (office, entertainment, car, public place) | 600 (550 adult speakers and 50 child speakers) | 4 | 170,000 | Available on request | 16 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 290 prompts per adult speaker and 210 prompts per child speaker including digits, natural numbers, letter strings, personal, place and business names, application words for adult speakers, command (toy, phone and general) for child speakers, phonetically rich words and sentences and free and elicited spontaneous responses for adult speakers | English (United States) scripted microphone |
| 106 | English (United States) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 62 hours | Add Quote | USE_ASR001 | Appen Global | Scripted Speech | English | United States | Low background noise (studio) | 200 | 2 | 80,000 | 18,318 | 48 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words Each speaker read 400 prompts including digits, natural numbers, personal and city names, telephone numbers, generic command and control items, phonetically rich sentences and words | English (United States) scripted microphone |
| 131 | English NER news text | Text | NER, Content Classification, Search Engines | N/A | 22,768 sentences | Add Quote | ENG_NER001 | Appen Global | News NER | English | N/A | N/A | N/A | N/A | 22,768 | Available on request | N/A | text | English NER news text | |
| 32 | Farsi/Persian (Iran) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 30 hours | Add Quote | FAR_ASR002 | Appen Global | Conversational Speech | Iranian Persian | Iran | Mixed | 1,000 | 2 | Available on request | 12,358 | 8 | wav | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words | Farsi/Persian (Iran) conversational telephony |
| 31 | Farsi/Persian (Iran) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 85 hours | Add Quote | FAR_ASR001 | Appen Global | Scripted Speech | Iranian Persian | Iran | Mixed | 789 | 1 | 38,400 | 8,716 | 8 | alaw | Fully transcribed to OrienTel type conventions Dataset is accompanied by a pronunciation lexicon [SAMPA] containing all transcribed words 48 prompts per speaker including digits, natural numbers, letter strings, personal, place, and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words | Farsi/Persian (Iran) scripted telephony |
| 135 | Farsi/Persian NER news text | Text | NER, Content Classification, Search Engines | N/A | 19,584 sentences | Add Quote | FAR_NER001 | Appen Global | News NER | Iranian Persian | Iran | N/A | N/A | N/A | 19,584 | Available on request | N/A | text | Farsi/Persian NER news text | |
| 185 | Finnish (Finland) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 10,000 words | Add Quote | fin_FIN_POS | Appen Global | Part of Speech Dictionary | Finnish | Finland | N/A | N/A | N/A | N/A | 10,000 | N/A | text | Finnish (Finland) Part of Speech Dictionary | |
| 128 | Finnish (Finland) printed text OCR | Image | Document Processing, Document Search | Camera | 7293 images | Add Quote | IMG_OCR_FIN_CN | Appen China | Document OCR | Finnish | Finland | Mixed lighting conditions | 4 | NA | NA | NA | NA | jpg | Images containing text, such as billboards / outer packaging / signage / magazines / menus, etc. | Finnish (Finland) printed text OCR |
| 184 | Finnish (Finland) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 85,000 words | Add Quote | fin_FIN_PHON | Appen Global | Pronunciation Dictionary | Finnish | Finland | N/A | N/A | N/A | N/A | 85,000 | N/A | text | Finnish (Finland) Pronunciation Dictionary | |
| 145 | French (Algeria) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 4,000 words | Add Quote | fra_DZA_PHON | Appen Global | Pronunciation Dictionary | French | Algeria | N/A | N/A | N/A | N/A | 4,000 | N/A | text | Arabic script | French (Algeria) Pronunciation Dictionary |
| 5 | French (Belgium) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 76 hours | Add Quote | Belgian French SpeechDat(II) FDB-1000 (FIXED1BF) | Nuance | Scripted Speech | French | Belgium | Low background noise | 1,000 | 1 | 53,000 | Available on request | 8 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 53 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words and spontaneous items for control | French (Belgium) scripted telephony |
| 36 | French (Canada) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 9 hours | Add Quote | FRC_ASR003 | Appen Global | Conversational Speech | French | Canada | Mixed | 68 | 2 | Available on request | 6,022 | 8 | alaw | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words Average length of calls: 10-15 mins For the majority of calls, only one half of the conversation was collected and transcribed, however, for a smaller number of calls, both speakers (in-line/out-line) were collected and transcribed | French (Canada) conversational telephony |
| 186 | French (Canada) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 67,000 words | Add Quote | fra_CAN_PHON | Appen Global | Pronunciation Dictionary | French | Canada | N/A | N/A | N/A | N/A | 67,000 | N/A | text | French (Canada) Pronunciation Dictionary | |
| 35 | French (Canada) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 46 hours | Add Quote | FRC_ASR002 | Appen Global | Scripted Speech | French | Canada | Low background noise (home/office) | 150 | 1 | 22,500 | 10,755 | 16 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 150 prompts per speaker including digits, digit strings (randomly generated), addressses and phonetically rich sentences and words | French (Canada) scripted microphone |
| 34 | French (Canada) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone | 131 hours | Add Quote | FRC_ASR001 | Appen Global | Scripted Speech | French | Canada | Mixed | 1,000 | 1 | 100,000 | 11,697 | 8 | alaw | Fully transcribed to SpeechDAT type conventions Dataset is accompanied by a pronunciation lexicon [SAMPA] containing all transcribed words 100 prompts per speaker including digits, natural numbers, letter strings, personal, place, and business names, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words | French (Canada) scripted telephony |
| 40 | French (France) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 25 hours | Add Quote | FRF_ASR001 | Appen Global | Conversational Speech | French | France | Low background noise | 563 | 2 | Available on request | 11,922 | 8 | alaw | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words For the majority of calls, both speakers (in-line/out-line) were collected and transcribed, however, for a smaller number of calls, only one half of the conversation was collected and transcribed | French (France) conversational telephony |
| 39 | French (France) In-Car | Audio | ASR, Virtual Assistant, In Car HMI & Entertainment | Microphone and mobile phone | Add Quote | French SpeechDat-Car | Nuance | Scripted Speech | French | France | Mixed (in-car) | 300 | 5 | 37,500 | Available on request | 16 and 8 | Available on request | Dataset is fully transcribed and is accompanied by a pronunciation lexicon and validation report Approximately 125 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names (some spontaneous), generic command and control items, phonetically rich words and sentences and prompts for spontaneous speech | French (France) In-Car | |
| 188 | French (France) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 95,000 words | Add Quote | fra_FRA_POS | Appen Global | Part of Speech Dictionary | French | France | N/A | N/A | N/A | N/A | 95,000 | N/A | text | French (France) Part of Speech Dictionary | |
| 187 | French (France) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 112,000 words | Add Quote | fra_FRA_PHON | Appen Global | Pronunciation Dictionary | French | France | N/A | N/A | N/A | N/A | 112,000 | N/A | text | French (France) Pronunciation Dictionary | |
| 41 | French (France) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 26 hours | Add Quote | FRF_ASR003 | Global Phone | Scripted Speech | French | France | Low background noise (home/office) | 98 | 1 | 10,273 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | French (France) scripted microphone |
| 37 | French (France) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 41 hours | Add Quote | French SpeechDat(II) FDB-1000 | Nuance | Scripted Speech | French | France | Low background noise (home/office) | 1,017 | 1 | 48,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 48 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | French (France) scripted telephony |
| 38 | French (France) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 305 hours | Add Quote | French SpeechDat(II) FDB-5000 | Nuance | Scripted Speech | French | France | Low background noise | 5,040 | 1 | 237,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 47 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | French (France) scripted telephony |
| 60 | French (Luxembourg) telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 45 hours | Add Quote | Luxembourgish French SpeechDat(II) FDB-500 (FIXED1LF) | Nuance | Scripted Speech | French | Luxembourg | Low background noise | 614 | 1 | 32,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 53 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | French (Luxembourg) telephony |
| 189 | German (Germany) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 146,000 words | Add Quote | deu_DEU_PHON | Appen Global | Pronunciation Dictionary | German | Germany | N/A | N/A | N/A | N/A | 146,000 | N/A | text | German (Germany) Pronunciation Dictionary | |
| 16 | German (Germany) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 16 hours | Add Quote | DEU_ASR001 | Appen Global | Scripted Speech | German | Germany | Low background noise (studio) | 127 | 2 | 12,700 | 6,826 | 16 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words Each speaker read 100 prompts including digits, natural numbers, personal and city names, telephone numbers, generic command and control items, phonetically rich sentences and words | German (Germany) scripted microphone |
| 18 | German (Germany) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 25 hours | Add Quote | DEU_ASR003 | Global Phone | Scripted Speech | German | Germany | Low background noise (home/office) | 77 | 1 | 10,085 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | German (Germany) scripted microphone |
| 42 | German (Germany) telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 31 hours | Add Quote | German SpeechDat (II) FDB-1000 | Nuance | Scripted Speech | German | Germany | Low background noise (home/office) | 988 | 1 | 43,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 44 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | German (Germany) telephony |
| 43 | German (Germany) telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 268 hours | Add Quote | German SpeechDat(II) FDB-4000 | Nuance | Scripted Speech | German | Germany | Low background noise (home/office) | 4,000 | 1 | 160,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 40 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | German (Germany) telephony |
| 61 | German (Luxembourg) telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 33 hours | Add Quote | Luxembourgish German SpeechDat(II) FDB-500 (FIXED1LG) | Nuance | Scripted Speech | German | Luxembourg | Low background noise | 500 | 1 | 26,500 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 53 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | German (Luxembourg) telephony |
| 190 | German (Switzerland) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | deu_CHE_PHON | Appen Global | Pronunciation Dictionary | German | Switzerland | N/A | N/A | N/A | N/A | 15,000 | N/A | text | German (Switzerland) Pronunciation Dictionary | |
| 94 | German (Switzerland) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 53 hours | Add Quote | Speecon German (Switzerland) database | Nuance | Scripted Speech | German | Switzerland | Mixed (office, entertainment, car, public place) | 600 (550 adult speakers and 50 child speakers) | 4 | 170,000 | Available on request | 16 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 290 prompts per adult speaker and 210 prompts per child speaker including digits, natural numbers, letter strings, personal, place and business names, application words for adult speakers, command (toy, phone and general) for child speakers, phonetically rich words and sentences and free and elicited spontaneous responses for adult speakers | German (Switzerland) scripted microphone |
| 68 | German (Turkey) telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 31 hours | Add Quote | OrienTel German Spoken by Turkish | Nuance | Scripted Speech | German | Turkey | Low background noise | 300 | 1 | 15,600 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 52 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | German (Turkey) telephony |
| 191 | Greek (Greece) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 5,000 words | Add Quote | ell_GRC_PHON | Appen Global | Pronunciation Dictionary | Greek | Greece | N/A | N/A | N/A | N/A | 5,000 | N/A | text | Greek (Greece) Pronunciation Dictionary | |
| 118 | Greek (Greece) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 191 hours | Add Quote | GRE_ASR001_CN | Appen China | Scripted Speech | Greek | Greece | Low background noise (home/office) | 287 | 1 | 54,113 | 68,271 | 16 | wav | Dataset is fully transcribed | Greek (Greece) scripted smartphone |
| 192 | Guarani (Paraguay) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 35,000 words | Add Quote | grn_PRY_PHON | Appen Global | Pronunciation Dictionary | Guarani | Paraguay | N/A | N/A | N/A | N/A | 35,000 | N/A | text | Guarani (Paraguay) Pronunciation Dictionary | |
| 194 | Haitian Creole (Haiti) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | hat_HTI_PHON | Appen Global | Pronunciation Dictionary | Haitian Creole | Haiti | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Haitian Creole (Haiti) Pronunciation Dictionary | |
| 45 | Hausa (Nigeria) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone | 33 hours | Add Quote | HAU_ASR002 | Appen Global | Conversational Speech | Hausa | Nigeria | Low background noise | 200 | 2 | Available on request | 7,949 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Hausa (Nigeria) conversational telephony |
| 195 | Hausa (Nigeria) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 11,000 words | Add Quote | hau_NGA_PHON | Appen Global | Pronunciation Dictionary | Hausa | Nigeria | N/A | N/A | N/A | N/A | 11,000 | N/A | text | Hausa (Nigeria) Pronunciation Dictionary | |
| 44 | Hausa scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 20 hours | Add Quote | HAU_ASR001 | Global Phone | Scripted Speech | Hausa | Multiple | Low background noise (home/office) | 103 | 1 | 7,895 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Hausa scripted microphone |
| 46 | Hebrew (Israel) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 34 hours | Add Quote | HEB_ASR001 | Appen Global | Conversational Speech | Hebrew | Israel | Low background noise | 200 | 2 | Available on request | 19,250 | 8 | alaw or wav | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Hebrew (Israel) conversational telephony |
| 196 | Hebrew (Israel) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 31,000 words | Add Quote | heb_ISR_PHON | Appen Global | Pronunciation Dictionary | Hebrew | Israel | N/A | N/A | N/A | N/A | 31,000 | N/A | text | Hebrew (Israel) Pronunciation Dictionary | |
| 48 | Hindi (India) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 32 hours | Add Quote | HIN_ASR002 | Appen Global | Conversational Speech | Hindi | India | Mixed | 996 | 2 | Available on request | 12,266 | 8 | wav | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words For the majority of calls, both speakers (in-line/out-line) were collected and transcribed, however, for a smaller number of calls, only one half of the conversation was collected and transcribed | Hindi (India) conversational telephony |
| 197 | Hindi (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 35,000 words | Add Quote | hin_IND_PHON | Appen Global | Pronunciation Dictionary | Hindi | India | N/A | N/A | N/A | N/A | 35,000 | N/A | text | Hindi (India) Pronunciation Dictionary | |
| 47 | Hindi (India) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone | 224 hours | Add Quote | HIN_ASR001 | Appen Global | Scripted Speech | Hindi | India | Low background noise | 1,920 | 1 | 96,000 | 9,853 | 8 | alaw | Fully transcribed to SpeechDAT type conventions Dataset is accompanied by a pronunciation lexicon [SAMPA] containing all transcribed words 50 prompts per speaker including digits, natural numbers, personal, business and place names, web addresses, confirmation items (yes, no + fuzzy), generic command and control items, phonetically rich sentences and words | Hindi (India) scripted telephony |
| 129 |  Human body movement | Video | Fitness Applications, Action Classification, Gesture Recognition | Mobile phone | 2000 videos | Add Quote | VED_HUMAN_BODY_CN | Appen China | Human Body | N/A | China | Mixed background and lighting conditions | 1000 | NA | NA | NA | NA | mp4 | Video clips are approximately 10-20 seconds long | Human body movement |
| 198 | Hungarian (Hungary) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 500 words | Add Quote | hun_HUN_PHON | Appen Global | Pronunciation Dictionary | Hungarian | Hungary | N/A | N/A | N/A | N/A | 500 | N/A | text | Hungarian (Hungary) Pronunciation Dictionary | |
| 119 | Hungarian (Hungary) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 286 hours | Add Quote | HUN_ASR001_CN | Appen China | Scripted Speech | Hungarian | Hungary | Low background noise (home/office) | 254 | 1 | 94,031 | 201,921 | 16 | wav | Dataset is fully transcribed | Hungarian (Hungary) scripted smartphone |
| 49 | Hungarian (Hungary) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 65 hours | Add Quote | Hungarian SpeechDat(E) | Nuance | Scripted Speech | Hungarian | Hungary | Low background noise | 1,000 | 1 | 48,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 48 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | Hungarian (Hungary) scripted telephony |
| 199 | Igbo (Nigeria) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 30,000 words | Add Quote | ibo_NGA_PHON | Appen Global | Pronunciation Dictionary | Igbo | Nigeria | N/A | N/A | N/A | N/A | 30,000 | N/A | text | Igbo (Nigeria) Pronunciation Dictionary | |
| 152 | Indonesian (Indonesia) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 10,000 words | Add Quote | ind_IDN_POS | Appen Global | Part of Speech Dictionary | Indonesian | Indonesia | N/A | N/A | N/A | N/A | 10,000 | N/A | text | Indonesian (Indonesia) Part of Speech Dictionary | |
| 151 | Indonesian (Indonesia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 95,000 words | Add Quote | ind_IDN_PHON | Appen Global | Pronunciation Dictionary | Indonesian | Indonesia | N/A | N/A | N/A | N/A | 95,000 | N/A | text | Indonesian (Indonesia) Pronunciation Dictionary | |
| 183 | Iranian Persian (Iran) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 1,400,000 words | Add Quote | pes_IRN_POS | Appen Global | Part of Speech Dictionary | Iranian Persian | Iran | N/A | N/A | N/A | N/A | 1,400,000 | N/A | text | Iranian Persian (Iran) Part of Speech Dictionary | |
| 182 | Iranian Persian (Iran) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 80,000 words | Add Quote | pes_IRN_PHON | Appen Global | Pronunciation Dictionary | Iranian Persian | Iran | N/A | N/A | N/A | N/A | 80,000 | N/A | text | Iranian Persian (Iran) Pronunciation Dictionary | |
| 52 | Italian (Italy) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 36 hours | Add Quote | ITA_ASR003 | Appen Global | Conversational Speech | Italian | Italy | Low background noise | 200 | 2 | Available on request | 18,974 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Italian (Italy) conversational telephony |
| 201 | Italian (Italy) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 147,000 words | Add Quote | ita_ITA_POS | Appen Global | Part of Speech Dictionary | Italian | Italy | N/A | N/A | N/A | N/A | 147,000 | N/A | text | Italian (Italy) Part of Speech Dictionary | |
| 200 | Italian (Italy) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 197,000 words | Add Quote | ita_ITA_PHON | Appen Global | Pronunciation Dictionary | Italian | Italy | N/A | N/A | N/A | N/A | 197,000 | N/A | text | Italian (Italy) Pronunciation Dictionary | |
| 50 | Italian (Italy) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 44 hours | Add Quote | ITA_ASR001 | Appen Global | Scripted Speech | Italian | Italy | Mixed | 200 | 4 | 40,000 | 7,316 | 22 | alaw | Fully transcribed to SpeechDAT type conventions Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 prompts per speaker including 100 command and control type items and 100 phonetically rich sentences | Italian (Italy) scripted microphone |
| 51 | Italian (Italy) scripted microphone | Audio | ASR, Virtual Assistant, In Car HMI & Entertainment | Microphone | 47 hours | Add Quote | ITA_ASR002 | Appen Global | Scripted Speech | Italian | Italy | Mixed (in-car) | 103 | 4 | 35,875 | 10,366 | 48 | alaw | Fully transcribed to SpeechDAT type conventions Dataset is accompanied by a pronunciation lexicon containing all transcribed words 350 prompts per speaker including digits, street names, generic command and control items, phonetically rich sentences and words Each speaker recorded 1or 2 sessions including Session 1 in a parked vehicle with the engine running and Session 2 in a vehicle travelling at 60 mph (100 km/h) | Italian (Italy) scripted microphone |
| 53 | Italian (Italy) scripted microphone | Audio | TTS | Microphone | 3 hours | Add Quote | ITA_TTS001 | Appen Global | Scripted Speech | Italian | Italy | Low background noise (studio) | 1 | 1 | 3,300 | Available on request | 22 | alaw | Dataset is accompanied by a pronunciation lexicon containing all words spoken in the Dataset 3,300 prompts per speaker including phonetically rich sentences | Italian (Italy) scripted microphone |
| 54 | Italian (Italy) telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 38 hours | Add Quote | Italian Fixed Network Speech SpeechDat(M) Corpus | Nuance | Scripted Speech | Italian | Italy | Low background noise (home/office) | 1,000 | 1 | 39,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 39 prompts per speaker includign isolated and connected digits, natural numbers, money amounts, spelled words, time and date phrases, yes/no questions, city names, common application words, application words in phrases and phonetically rich sentences | Italian (Italy) telephony |
| 55 | Italian (Italy) telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 228 hours | Add Quote | Italian SpeechDat(II) FDB-3000 | Nuance | Scripted Speech | Italian | Italy | Low background noise (home/office) | 3,040 | 1 | 134,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 44 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | Italian (Italy) telephony |
| 56 | Italian (Italy) telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone | 103 hours | Add Quote | Italian SpeechDat(II) MDB-250 | Nuance | Scripted Speech | Italian | Italy | Low background noise (home/office) | 375 | 1 | 19,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 51 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | Italian (Italy) telephony |
| 89 | Italian (Italy) telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone | 13 hours | Add Quote | SpeechDat(M) Italian Mobile Network Speech Database | Nuance | Scripted Speech | Italian | Italy | Low background noise (home/office) | 342 | 1 | 13,500 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 40 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | Italian (Italy) telephony |
| 203 | Japanese (Japan) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 265,000 words | Add Quote | jpn_JPN_POS | Appen Global | Part of Speech Dictionary | Japanese | Japan | N/A | N/A | N/A | N/A | 265,000 | N/A | text | Japanese (Japan) Part of Speech Dictionary | |
| 202 | Japanese (Japan) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 262,000 words | Add Quote | jpn_JPN_PHON | Appen Global | Pronunciation Dictionary | Japanese | Japan | N/A | N/A | N/A | N/A | 262,000 | N/A | text | Japanese (Japan) Pronunciation Dictionary | |
| 57 | Japanese (Japan) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 33 hours | Add Quote | JPN_ASR001 | Global Phone | Scripted Speech | Japanese | Japan | Low background noise (home/office) | 144 | 1 | 13,067 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Japanese (Japan) scripted microphone |
| 95 | Japanese (Japan) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 57 hours | Add Quote | Speecon Japanese | Nuance | Scripted Speech | Japanese | Japan | Mixed (office, entertainment, car, public place) | 600 (550 adult speakers and 50 child speakers) | 4 | 170,000 | Available on request | 16 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 290 prompts per adult speaker and 210 prompts per child speaker including digits, natural numbers, letter strings, personal, place and business names, application words for adult speakers, command (toy, phone and general) for child speakers, phonetically rich words and sentences and free and elicited spontaneous responses for adult speakers | Japanese (Japan) scripted microphone |
| 136 | Japanese NER news text | Text | NER, Content Classification, Search Engines | N/A | 20,629 sentences | Add Quote | JPY_NER001 | Appen Global | News NER | Japanese | Japan | N/A | N/A | N/A | 20,629 | Available on request | N/A | text | Japanese NER news text | |
| 204 | Javanese (Indonesia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 20,000 words | Add Quote | jav_IDN_PHON | Appen Global | Pronunciation Dictionary | Javanese | Indonesia | N/A | N/A | N/A | N/A | 20,000 | N/A | text | Javanese (Indonesia) Pronunciation Dictionary | |
| 58 | Kannada (India) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 15 hours | Add Quote | KAN_ASR001 | Appen Global | Conversational Speech | Kannada | India | Mixed | 178 | 2 | Available on request | 15,660 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words | Kannada (India) conversational telephony |
| 109 | Kannada (India) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 57 hours | Add Quote | KAN_ASR001A | Appen Global | Conversational Speech | Kannada | India | Mixed | 1,000 | 2 | Available on request | 15,660 | 8 | alaw | Approx. 25% of the dataset sessions are transcribed and time stamped - full transcripts can be made available Database is accompanied by a pronunciation lexicon containing all transcribed words | Kannada (India) conversational telephony |
| 205 | Kannada (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 35,000 words | Add Quote | kan_IND_PHON | Appen Global | Pronunciation Dictionary | Kannada | India | N/A | N/A | N/A | N/A | 35,000 | N/A | text | Kannada (India) Pronunciation Dictionary | |
| 206 | Kazakh (Kazakhstan) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 30,000 words | Add Quote | kaz_KAZ_PHON | Appen Global | Pronunciation Dictionary | Kazakh | Kazakhstan | N/A | N/A | N/A | N/A | 30,000 | N/A | text | Kazakh (Kazakhstan) Pronunciation Dictionary | |
| 123 | Khmer (Cambodia) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 90 hours | Add Quote | KHM_ASR001_CN | Appen China | Scripted Speech | Central Khmer | Cambodia | Low background noise (home/office) | 94 | 1 | 24,618 | 52,157 | 16 | wav | Dataset is fully transcribed | Khmer (Cambodia) scripted smartphone |
| 208 | Korean (South Korea) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 100,000 words | Add Quote | kor_KOR_POS | Appen Global | Part of Speech Dictionary | Korean | South Korea | N/A | N/A | N/A | N/A | 100,000 | N/A | text | Korean (South Korea) Part of Speech Dictionary | |
| 207 | Korean (South Korea) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 100,000 words | Add Quote | kor_KOR_PHON | Appen Global | Pronunciation Dictionary | Korean | South Korea | N/A | N/A | N/A | N/A | 100,000 | N/A | text | Korean (South Korea) Pronunciation Dictionary | |
| 59 | Korean (South Korea) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 20 hours | Add Quote | KOR_ASR001 | Global Phone | Scripted Speech | Korean | South Korea | Low background noise (home/office) | 100 | 1 | 8,107 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Korean (South Korea) scripted microphone |
| 132 | Korean NER news text | Text | NER, Content Classification, Search Engines | N/A | 25,830 sentences | Add Quote | KOR_NER001 | Appen Global | News NER | Korean | South Korea | N/A | N/A | N/A | 25,830 | Available on request | N/A | text | Korean NER news text | |
| 209 | Kurmanji (Turkey) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 60,000 words | Add Quote | kur_TUR_PHON | Appen Global | Pronunciation Dictionary | Kurmanji | Turkey | N/A | N/A | N/A | N/A | 60,000 | N/A | text | Kurmanji (Turkey) Pronunciation Dictionary | |
| 210 | Lao (Laos) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 9,000 words | Add Quote | lao_LAO_PHON | Appen Global | Pronunciation Dictionary | Lao | Laos | N/A | N/A | N/A | N/A | 9,000 | N/A | text | Lao (Laos) Pronunciation Dictionary | |
| 211 | Lithuanian (Lithuania) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 60,000 words | Add Quote | lit_LTU_PHON | Appen Global | Pronunciation Dictionary | Lithuanian | Lithuania | N/A | N/A | N/A | N/A | 60,000 | N/A | text | Lithuanian (Lithuania) Pronunciation Dictionary | |
| 212 | Malayalam (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 4,000 words | Add Quote | mal_IND_PHON | Appen Global | Pronunciation Dictionary | Malayalam | India | N/A | N/A | N/A | N/A | 4,000 | N/A | text | Malayalam (India) Pronunciation Dictionary | |
| 213 | Malaysian (Malaysia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 10,000 words | Add Quote | msa_MYS_PHON | Appen Global | Pronunciation Dictionary | Malaysian | Malaysia | N/A | N/A | N/A | N/A | 10,000 | N/A | text | Malaysian (Malaysia) Pronunciation Dictionary | |
| 214 | Mandarin (Simplified) (China) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 35,000 words | Add Quote | zho_CHN_PHON | Appen Global | Pronunciation Dictionary | Mandarin (Simplified) | China | N/A | N/A | N/A | N/A | 35,000 | N/A | text | Mandarin (Simplified) (China) Pronunciation Dictionary | |
| 215 | Mandarin (Traditional) (Taiwan) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 50,000 words | Add Quote | zho_TWN_PHON | Appen Global | Pronunciation Dictionary | Mandarin (Traditional) | Taiwan | N/A | N/A | N/A | N/A | 50,000 | N/A | text | Mandarin (Traditional) (Taiwan) Pronunciation Dictionary | |
| 63 | Mandarin Chinese (China) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 26 hours | Add Quote | MAC_ASR002 | Global Phone | Scripted Speech | Mandarin Chinese | China | Low background noise (home/office) | 132 | 1 | 10,225 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Mandarin Chinese (China) scripted microphone |
| 62 | Mandarin Chinese (China) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 323 hours | Add Quote | MAC_ASR001 | Appen Global | Scripted Speech | Mandarin Chinese | China | Mixed | 2,000 | 1 | 200,000 | 7,145 | 8 | alaw | Fully transcribed to SpeechDAT type conventions Dataset is accompanied by a pronunciation lexicon [SAMPA] containing all transcribed words 98 prompts per speaker including digits, natural numbers, letter strings, personal, place, and business names, confirmation items (yes, no + fuzzy), generic command and control items (from a set of 215), phonetically rich sentences and words | Mandarin Chinese (China) scripted telephony |
| 134 | Mandarin NER news text | Text | NER, Content Classification, Search Engines | N/A | 17,313 sentences | Add Quote | MAC_NER001 | Appen Global | News NER | Mandarin Chinese | China | N/A | N/A | N/A | 17,313 | Available on request | N/A | text | Mandarin NER news text | |
| 64 | Marathi (India) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 15 hours | Add Quote | MAR_ASR001 | Appen Global | Conversational Speech | Marathi | India | Mixed | 180 | 2 | Available on request | 11,908 | 8 | alaw | Approx. 29% of the dataset sessions are transcribed and time stamped - full transcripts can be made available Dataset is accompanied by a pronunciation lexicon containing all transcribed words | Marathi (India) conversational telephony |
| 110 | Marathi (India) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 52 hours | Add Quote | MAR_ASR001A | Appen Global | Conversational Speech | Marathi | India | Mixed | 1,000 | 2 | Available on request | 11,908 | 8 | alaw | Portion of the dataset sessions are transcribed and time stamped - full transcripts can be made available Dataset is accompanied by a pronunciation lexicon containing all transcribed words | Marathi (India) conversational telephony |
| 216 | Marathi (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 30,000 words | Add Quote | mar_IND_PHON | Appen Global | Pronunciation Dictionary | Marathi | India | N/A | N/A | N/A | N/A | 30,000 | N/A | text | Marathi (India) Pronunciation Dictionary | |
| 217 | Mongolian (Mongolia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 30,000 words | Add Quote | mon_MNG_PHON | Appen Global | Pronunciation Dictionary | Mongolian | Mongolia | N/A | N/A | N/A | N/A | 30,000 | N/A | text | Mongolian (Mongolia) Pronunciation Dictionary | |
| 219 | Norwegian (Norway) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 3,000 words | Add Quote | nor_NOR_POS | Appen Global | Part of Speech Dictionary | Norwegian | Norway | N/A | N/A | N/A | N/A | 3,000 | N/A | text | Norwegian (Norway) Part of Speech Dictionary | |
| 218 | Norwegian (Norway) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 115,000 words | Add Quote | nor_NOR_PHON | Appen Global | Pronunciation Dictionary | Norwegian | Norway | N/A | N/A | N/A | N/A | 115,000 | N/A | text | Norwegian (Norway) Pronunciation Dictionary | |
| 220 | Oriya (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | ori_IND_PHON | Appen Global | Pronunciation Dictionary | Oriya | India | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Oriya (India) Pronunciation Dictionary | |
| 80 | Panjabi (Pakistan) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 20 hours | Add Quote | PAP_ASR001 | Appen Global | Conversational Speech | Panjabi | Pakistan | Low background noise | 205 | 2 | Available on request | 7,298 | 8 | alaw | Dataset is fully transcribed and time-stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 71% of calls, both speakers (in-line/out-line) were collected and transcribed, however, for 29% calls, only one half of the conversation was collected and transcribed | Panjabi (Pakistan) conversational telephony |
| 74 | Pashto (Afghanistan) broadcast | Audio | ASR, Automatic Captioning, Keyword Spotting | Microphone | 51 hours | Add Quote | PAS_BRC001 | Appen Global | Broadcast Speech | Northern Pashto; Southern Pashto | Afghanistan | Low background noise (studio) | N/A | 1 | Available on request | Available on request | N/A | wav | Dataset is fully transcribed and timestamped Dataset is largely speech only and does not include music or advertisements Data types include: talk shows, interviews, news broadcasts (excluding news reading by anchors) | Pashto (Afghanistan) broadcast |
| 73 | Pashto (Afghanistan) conversational microphone | Audio | ASR, Conversational AI, Speech Analytics | Microphone | 39 hours | Add Quote | PAS_ASR002 | Appen Global | Conversational Speech | Northern Pashto; Southern Pashto | Afghanistan | Low background noise | 40 | 2 | Available on request | 9,480 | 16 | wav | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words A full translation of the transcripts into French is also available as an optional additional purchase Average length of calls: 120 mins where one speaker acts as an interviewer and the other as the interviewee for scenarios are similar to TransTAC style (e.g. civil affairs, checkpoints etc.) The interviewer appears in more than one set of dialogues but the interviewee is unique for each set | Pashto (Afghanistan) conversational microphone |
| 72 | Pashto (Afghanistan) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 55 hours | Add Quote | PAS_ASR001 | Appen Global | Conversational Speech | Northern Pashto; Southern Pashto | Afghanistan | Low background noise | 967 | 2 | Available on request | 13,633 | 8 | wav | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words For the majority of calls, both speakers (in-line/out-line) were collected and transcribed, however, for a smaller number of calls, only one half of the conversation was collected and transcribed | Pashto (Afghanistan) conversational telephony |
| 221 | Pashto (Afghanistan) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 65,000 words | Add Quote | pus_AFG_PHON | Appen Global | Pronunciation Dictionary | Pashto | Afghanistan | N/A | N/A | N/A | N/A | 65,000 | N/A | text | Pashto (Afghanistan) Pronunciation Dictionary | |
| 223 | Polish (Poland) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 4,000 words | Add Quote | pol_POL_POS | Appen Global | Part of Speech Dictionary | Polish | Poland | N/A | N/A | N/A | N/A | 4,000 | N/A | text | Polish (Poland) Part of Speech Dictionary | |
| 222 | Polish (Poland) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 40,000 words | Add Quote | pol_POL_PHON | Appen Global | Pronunciation Dictionary | Polish | Poland | N/A | N/A | N/A | N/A | 40,000 | N/A | text | Polish (Poland) Pronunciation Dictionary | |
| 75 | Polish (Poland) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 25 hours | Add Quote | POL_ASR001 | Global Phone | Scripted Speech | Polish | Poland | Low background noise (home/office) | 99 | 1 | 10,130 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Polish (Poland) scripted microphone |
| 120 | Polish (Poland) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 293 hours | Add Quote | POL_ASR002_CN | Appen China | Scripted Speech | Polish | Poland | Low background noise (home/office) | 353 | 1 | 106,674 | 168,544 | 16 | wav | Dataset is fully transcribed | Polish (Poland) scripted smartphone |
| 76 | Polish (Poland) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 78 hours | Add Quote | Polish SpeechDat(E) Database | Nuance | Scripted Speech | Polish | Poland | Low background noise | 1,000 | 1 | 48,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 48 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | Polish (Poland) scripted telephony |
| 78 | Portuguese (Brazil) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 33 hours | Add Quote | PTB_ASR002 | Appen Global | Conversational Speech | Portuguese | Brazil | Low background noise | 200 | 2 | Available on request | 11,287 | 8 | alaw | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words | Portuguese (Brazil) conversational telephony |
| 77 | Portuguese (Brazil) microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 26 hours | Add Quote | PTB_ASR001 | Global Phone | Scripted Speech | Portuguese | Brazil | Low background noise (home/office) | 102 | 1 | 10,417 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Portuguese (Brazil) microphone |
| 225 | Portuguese (Brazil) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 100,000 words | Add Quote | por_BRA_POS | Appen Global | Part of Speech Dictionary | Portuguese | Brazil | N/A | N/A | N/A | N/A | 100,000 | N/A | text | Portuguese (Brazil) Part of Speech Dictionary | |
| 224 | Portuguese (Brazil) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 102,000 words | Add Quote | por_BRA_PHON | Appen Global | Pronunciation Dictionary | Portuguese | Brazil | N/A | N/A | N/A | N/A | 102,000 | N/A | text | Portuguese (Brazil) Pronunciation Dictionary | |
| 79 | Portuguese (Portugal) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 36 hours | Add Quote | PTP_ASR001 | Appen Global | Conversational Speech | Portuguese | Portugal | Low background noise | 200 | 2 | Available on request | 16,339 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Portuguese (Portugal) conversational telephony |
| 227 | Portuguese (Portugal) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 100,000 words | Add Quote | por_PRT_POS | Appen Global | Part of Speech Dictionary | Portuguese | Portugal | N/A | N/A | N/A | N/A | 100,000 | N/A | text | Portuguese (Portugal) Part of Speech Dictionary | |
| 226 | Portuguese (Portugal) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 112,000 words | Add Quote | por_PRT_PHON | Appen Global | Pronunciation Dictionary | Portuguese | Portugal | N/A | N/A | N/A | N/A | 112,000 | N/A | text | Portuguese (Portugal) Pronunciation Dictionary | |
| 81 | Romanian (Romania) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 37 hours | Add Quote | ROM_ASR001 | Appen Global | Conversational Speech | Romanian | Romania | Low background noise | 200 | 2 | Available on request | 16,658 | 8 | alaw | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Romanian (Romania) conversational telephony |
| 228 | Romanian (Romania) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | ron_ROU_PHON | Appen Global | Pronunciation Dictionary | Romanian | Romania | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Romanian (Romania) Pronunciation Dictionary | |
| 82 | Russian (Russia) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 37 hours | Add Quote | RUS_ASR001 | Appen Global | Conversational Speech | Russian | Russia | Low background noise | 200 | 2 | Available on request | 28,284 | 8 | alaw or wav | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Russian (Russia) conversational telephony |
| 230 | Russian (Russia) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 100,000 words | Add Quote | rus_RUS_POS | Appen Global | Part of Speech Dictionary | Russian | Russia | N/A | N/A | N/A | N/A | 100,000 | N/A | text | Russian (Russia) Part of Speech Dictionary | |
| 229 | Russian (Russia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 115,000 words | Add Quote | rus_RUS_PHON | Appen Global | Pronunciation Dictionary | Russian | Russia | N/A | N/A | N/A | N/A | 115,000 | N/A | text | Russian (Russia) Pronunciation Dictionary | |
| 83 | Russian (Russia) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 31 hours | Add Quote | RUS_ASR002 | Global Phone | Scripted Speech | Russian | Russia | Low background noise (home/office) | 115 | 1 | 12,205 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Russian (Russia) scripted microphone |
| 96 | Russian (Russia) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 46 hours | Add Quote | Speecon Russian Database | Nuance | Scripted Speech | Russian | Russia | Mixed (office, entertainment, car, public place) | 600 (550 adult speakers and 50 child speakers) | 4 | 170,000 | Available on request | 16 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 290 prompts per adult speaker and 210 prompts per child speaker including digits, natural numbers, letter strings, personal, place and business names, application words for adult speakers, command (toy, phone and general) for child speakers, phonetically rich words and sentences and free and elicited spontaneous responses for adult speakers | Russian (Russia) scripted microphone |
| 84 | Russian (Russia) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 180 hours | Add Quote | Russian SpeechDat(E) Database | Nuance | Scripted Speech | Russian | Russia | Low background noise | 2,500 | 1 | 112,000 | Available on request | 8 | alaw | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 45 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | Russian (Russia) scripted telephony |
| 133 | Russian NER news text | Text | NER, Content Classification, Search Engines | N/A | 29,888 sentences | Add Quote | RUS_NER001 | Appen Global | News NER | Russian | Russia | N/A | N/A | N/A | 29,888 | Available on request | N/A | text | Russian NER news text | |
| 231 | Serbian (Serbia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | srp_SRB_PHON | Appen Global | Pronunciation Dictionary | Serbian | Serbia | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Serbian (Serbia) Pronunciation Dictionary | |
| 126 | Simplified Chinese printed text OCR | Image | Document Processing, Document Search | Camera | 200 images | Add Quote | IMG_OCR_MAC_CN | Appen China | Document OCR | N/A | China | Mixed lighting conditions | 30 | NA | NA | NA | NA | jpg | Text in each image is labeled with bounding boxes by the line Images containing heavy text in Chinese, including books, publications, posters, receipts, PPT, printed paper, etc. | Simplified Chinese printed text OCR |
| 85 | Slovak (Slovakia) scripted telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 65 hours | Add Quote | Slovak SpeechDat(E) Database | Nuance | Scripted Speech | Slovak | Slovakia | Low background noise | 1,000 | 1 | 48,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 48 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | Slovak (Slovakia) scripted telephony |
| 86 | Slovenian (Slovenian) telephony | Audio | ASR, Call Centre, Virtual Assistant | Landline only | 76 hours | Add Quote | Slovenian SpeechDat(II) FDB-1000 | Nuance | Scripted Speech | Slovenian | Slovenia | Low background noise (home/office) | 1,000 | 1 | 40,000 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report Approximately 40 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | Slovenian (Slovenian) telephony |
| 87 | Somali (Somalia) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 50 hours | Add Quote | SOM_ASR001 | Appen Global | Conversational Speech | Somali | Somalia | Low background noise | 1,000 | 2 | Available on request | 23,217 | 8 | alaw | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words | Somali (Somalia) conversational telephony |
| 232 | Somali (Somalia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 76,000 words | Add Quote | som_SOM_PHON | Appen Global | Pronunciation Dictionary | Somali | Somalia | N/A | N/A | N/A | N/A | 76,000 | N/A | text | Somali (Somalia) Pronunciation Dictionary | |
| 233 | Sorani (Iraq) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 25,000 words | Add Quote | kur_IRQ_PHON | Appen Global | Pronunciation Dictionary | Sorani | Iraq | N/A | N/A | N/A | N/A | 25,000 | N/A | text | Sorani (Iraq) Pronunciation Dictionary | |
| 88 | Sorani (Kurdish) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 5 hours | Add Quote | SOR_ASR001 | Appen Global | Conversational Speech | Central Kurdish (Iran) | Iran | Low background noise | 170 | 2 | Available on request | 7,924 | 8 | alaw or wav | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words For a large proportion of calls, only one half of the conversation was collected and transcribed | Sorani (Kurdish) conversational telephony |
| 234 | Spanish (Argentina) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | spa_ARG_PHON | Appen Global | Pronunciation Dictionary | Spanish | Argentina | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Spanish (Argentina) Pronunciation Dictionary | |
| 236 | Spanish (Chile) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | spa_CHL_PHON | Appen Global | Pronunciation Dictionary | Spanish | Chile | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Spanish (Chile) Pronunciation Dictionary | |
| 237 | Spanish (Colombia) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | spa_COL_PHON | Appen Global | Pronunciation Dictionary | Spanish | Colombia | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Spanish (Colombia) Pronunciation Dictionary | |
| 27 | Spanish (Latin America - Chile and Colombia) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 22 hours | Add Quote | ESL_ASR002 | Appen Global | Conversational Speech | Spanish | Chile; Columbia | Mixed | 84 | 2 | Available on request | Available on request | 8 | wav | Dataset is fully transcribed and time-stamped Call Centre style conversations (by 64 customers, 14 agents) in banking and telco domains, primarily using mobile phone | Spanish (Latin America - Chile and Colombia) conversational telephony |
| 26 | Spanish (Latin America) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 17 hours | Add Quote | ESL_ASR001 | Global Phone | Scripted Speech | Spanish | Costa Rica | Low background noise (home/office) | 100 | 1 | 6,898 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Spanish (Latin America) scripted microphone |
| 238 | Spanish (Peru) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | spa_PER_PHON | Appen Global | Pronunciation Dictionary | Spanish | Peru | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Spanish (Peru) Pronunciation Dictionary | |
| 235 | Spanish (Spain) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 100,000 words | Add Quote | spa_ESP_PHON | Appen Global | Pronunciation Dictionary | Spanish | Spain | N/A | N/A | N/A | N/A | 100,000 | N/A | text | Spanish (Spain) Pronunciation Dictionary | |
| 28 | Spanish (Spain) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 39 hours | Add Quote | ESP_ASR001 | Appen Global | Scripted Speech | Spanish | Spain | Mixed | 200 | 4 | 40,000 | 6,367 | 22 | alaw | Fully transcribed to SpeechDAT type conventions Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 prompts per speaker including 100 command and control type items and 100 phonetically rich sentences | Spanish (Spain) scripted microphone |
| 30 | Spanish (Spain) scripted microphone | Audio | TTS | Microphone | 1 hour | Add Quote | ESP_TTS001 | Appen Global | Scripted Speech | Spanish | Spain | Low background noise (studio) | 1 | 1 | 1,787 | 3,614 | 22 | alaw | Dataset is accompanied by a pronunciation lexicon containing all words spoken in the Dataset 1,787 prompts per speaker including phonetically rich sentences | Spanish (Spain) scripted microphone |
| 97 | Spanish (Spain) scripted microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 46 hours | Add Quote | Speecon Spanish Database | Nuance | Scripted Speech | Spanish | Spain | Mixed (office, entertainment, car, public place) | 600 (550 adult speakers and 50 child speakers) | 4 | 170,000 | Available on request | 16 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 290 prompts per adult speaker and 210 prompts per child speaker including digits, natural numbers, letter strings, personal, place and business names, application words for adult speakers, command (toy, phone and general) for child speakers, phonetically rich words and sentences and free and elicited spontaneous responses for adult speakers | Spanish (Spain) scripted microphone |
| 117 | Spanish (Spain) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 540 hours | Add Quote | ESP_ASR002_CN | Appen China | Scripted Speech | Spanish | Spain | Low background noise (home/office) | 347 | 1 | 258,395 | 134,939 | 16 | wav | Dataset is fully transcribed | Spanish (Spain) scripted smartphone |
| 239 | Spanish (United States) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 90,000 words | Add Quote | spa_USA_PHON | Appen Global | Pronunciation Dictionary | Spanish | United States | N/A | N/A | N/A | N/A | 90,000 | N/A | text | Spanish (United States) Pronunciation Dictionary | |
| 240 | Spanish (Venezuela) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 15,000 words | Add Quote | spa_VEN_PHON | Appen Global | Pronunciation Dictionary | Spanish | Venezuela | N/A | N/A | N/A | N/A | 15,000 | N/A | text | Spanish (Venezuela) Pronunciation Dictionary | |
| 241 | Swahili (Kenya) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 66,000 words | Add Quote | swa_KEN_PHON | Appen Global | Pronunciation Dictionary | Swahili | Kenya | N/A | N/A | N/A | N/A | 66,000 | N/A | text | Swahili (Kenya) Pronunciation Dictionary | |
| 243 | Swedish (Sweden) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 105,000 words | Add Quote | swe_SWE_POS | Appen Global | Part of Speech Dictionary | Swedish | Sweden | N/A | N/A | N/A | N/A | 105,000 | N/A | text | Swedish (Sweden) Part of Speech Dictionary | |
| 242 | Swedish (Sweden) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 100,000 words | Add Quote | swe_SWE_PHON | Appen Global | Pronunciation Dictionary | Swedish | Sweden | N/A | N/A | N/A | N/A | 100,000 | N/A | text | Swedish (Sweden) Pronunciation Dictionary | |
| 98 | Swedish (Sweden/ Finland) microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 30 hours | Add Quote | SWE_ASR001 | Global Phone | Scripted Speech | Swedish | Sweden; Finland | Low background noise (home/office) | 98 | 1 | 11,816 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Swedish (Sweden/ Finland) microphone |
| 244 | Sylheti (Bangladesh- India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 22,000 words | Add Quote | syl_BGD;IND_PHON | Appen Global | Pronunciation Dictionary | Sylheti | Bangladesh; India | N/A | N/A | N/A | N/A | 22,000 | N/A | text | Sylheti (Bangladesh- India) Pronunciation Dictionary | |
| 245 | Tagalog (Philippines) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 30,000 words | Add Quote | tgl_PHL_PHON | Appen Global | Pronunciation Dictionary | Tagalog | Philippines | N/A | N/A | N/A | N/A | 30,000 | N/A | text | Tagalog (Philippines) Pronunciation Dictionary | |
| 247 | Tamil (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 105,000 words | Add Quote | tam_IND_PHON | Appen Global | Pronunciation Dictionary | Tamil | India | N/A | N/A | N/A | N/A | 105,000 | N/A | text | Tamil (India) Pronunciation Dictionary | |
| 246 | Telugu (India) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 50,000 words | Add Quote | tel_IND_PHON | Appen Global | Pronunciation Dictionary | Telugu | India | N/A | N/A | N/A | N/A | 50,000 | N/A | text | Telugu (India) Pronunciation Dictionary | |
| 101 | Thai (Thailand) microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 28 hours | Add Quote | THA_ASR001 | Global Phone | Scripted Speech | Thai | Thailand | Low background noise (home/office) | 98 | 1 | 14,039 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Thai (Thailand) microphone |
| 127 | Thai (Thailand) printed text OCR | Image | Document Processing, Document Search | Camera | 1219 images | Add Quote | IMG_OCR_THA_CN | Appen China | Document OCR | Thai | Thailand | Mixed lighting conditions | 10 | NA | NA | NA | NA | jpg | Images containing text, Shopping receipts / tickets / invoices / taxi slips, etc. | Thai (Thailand) printed text OCR |
| 248 | Thai (Thailand) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 55,000 words | Add Quote | tha_THA_PHON | Appen Global | Pronunciation Dictionary | Thai | Thailand | N/A | N/A | N/A | N/A | 55,000 | N/A | text | Thai (Thailand) Pronunciation Dictionary | |
| 249 | Tok Pisin (Papua New Guinea) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 10,000 words | Add Quote | tpi_PNG_PHON | Appen Global | Pronunciation Dictionary | Tok Pisin | Papua New Guinea | N/A | N/A | N/A | N/A | 10,000 | N/A | text | Tok Pisin (Papua New Guinea) Pronunciation Dictionary | |
| 102 | Turkish (Turkey) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 41 hours | Add Quote | TUR_ASR001 | Appen Global | Conversational Speech | Turkish | Turkey | Low background noise | 200 | 2 | Available on request | 32,386 | 8 | alaw or wav | Dataset is fully transcribed and timestamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words 200 telephony conversations are recorded for this project - 100 speakers make 2 calls each (1 from landline, 1 from mobile) to a pool of 100 call receivers | Turkish (Turkey) conversational telephony |
| 103 | Turkish (Turkey) microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 17 hours | Add Quote | TUR_ASR002 | Global Phone | Scripted Speech | Turkish | Turkey | Low background noise (home/office) | 100 | 1 | 6,950 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Turkish (Turkey) microphone |
| 251 | Turkish (Turkey) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 257,000 words | Add Quote | tur_TUR_POS | Appen Global | Part of Speech Dictionary | Turkish | Turkey | N/A | N/A | N/A | N/A | 257,000 | N/A | text | Turkish (Turkey) Part of Speech Dictionary | |
| 250 | Turkish (Turkey) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 255,000 words | Add Quote | tur_TUR_PHON | Appen Global | Pronunciation Dictionary | Turkish | Turkey | N/A | N/A | N/A | N/A | 255,000 | N/A | text | Turkish (Turkey) Pronunciation Dictionary | |
| 121 | Turkish (Turkey) scripted smartphone | Audio | ASR, Virtual Assistant, Chatbot | Mobile phone | 739 hours | Add Quote | TUR_ASR003_CN | Appen China | Scripted Speech | Turkish | Turkey | Low background noise (home/office) | 664 | 1 | 185,706 | 215,135 | 16 | wav | Dataset is fully transcribed | Turkish (Turkey) scripted smartphone |
| 69 | Turkish (Turkey) telephony | Audio | ASR, Call Centre, Virtual Assistant | Mobile phone and landline | 118 hours | Add Quote | OrienTel Turkish Database | Nuance | Scripted Speech | Turkish | Turkey | Low background noise | 1,700 | 1 | 76,500 | Available on request | 8 | Available on request | Dataset is fully transcribed to SpeechDAT type conventions and is accompanied by a pronunciation lexicon and validation report 45 prompts per speaker including digits, natural numbers, letter strings, personal, place and business names, confirmation items (yes, no + fuzzy), generic command and control items and phonetically rich sentences and words | Turkish (Turkey) telephony |
| 252 | Ukrainian (Ukraine) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 5,000 words | Add Quote | ukr_UKR_PHON | Appen Global | Pronunciation Dictionary | Ukrainian | Ukraine | N/A | N/A | N/A | N/A | 5,000 | N/A | text | Ukrainian (Ukraine) Pronunciation Dictionary | |
| 105 | Urdu (India/ Pakistan) conversational telephony | Audio | ASR, Conversational AI, Speech Analytics | Mobile phone and landline | 47 hours | Add Quote | URD_ASR001 | Appen Global | Conversational Speech | Urdu | India; Pakistan | Mixed | 1,000 | 2 | Available on request | 10,871 | 8 | wav | Dataset is fully transcribed and time stamped Dataset is accompanied by a pronunciation lexicon containing all transcribed words | Urdu (India/ Pakistan) conversational telephony |
| 254 | Urdu (Pakistan) Part of Speech Dictionary | Text | ASR, TTS, Language Modelling | N/A | 12,000 words | Add Quote | urd_PAK_POS | Appen Global | Part of Speech Dictionary | Urdu | Pakistan | N/A | N/A | N/A | N/A | 12,000 | N/A | text | Urdu (Pakistan) Part of Speech Dictionary | |
| 253 | Urdu (Pakistan) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 40,000 words | Add Quote | urd_PAK_PHON | Appen Global | Pronunciation Dictionary | Urdu | Pakistan | N/A | N/A | N/A | N/A | 40,000 | N/A | text | Urdu (Pakistan) Pronunciation Dictionary | |
| 137 | Urdu NER news text | Text | NER, Content Classification, Search Engines | N/A | 20,634 sentences | Add Quote | URD_NER001 | Appen Global | News NER | Urdu | Pakistan | N/A | N/A | N/A | 20,634 | Available on request | N/A | text | Urdu NER news text | |
| 108 | Vietnamese (Vietnam) microphone | Audio | ASR, Virtual Assistant, Chatbot | Microphone | 47 hours | Add Quote | VIE_ASR001 | Global Phone | Scripted Speech | Vietnamese | Vietnam | Low background noise (home/office) | 129 | 1 | 18,842 | Available on request | 16 | wav | Dataset is fully transcribed and the transcription is available both in original script and in Romanized form Each speaker reads a number of phonetically rich sentences selected from national newspaper articles available from the web tocover a wide domain with large vocabulary Developed in collaboration with the Karlsruhe Institute of Technology (KIT) | Vietnamese (Vietnam) microphone |
| 255 | Vietnamese (Vietnam) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 8,000 words | Add Quote | vie_VNM_PHON | Appen Global | Pronunciation Dictionary | Vietnamese | Vietnam | N/A | N/A | N/A | N/A | 8,000 | N/A | text | Vietnamese (Vietnam) Pronunciation Dictionary | |
| 256 | Wu (China) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 10,000 words | Add Quote | wuu_CHN_PHON | Appen Global | Pronunciation Dictionary | Wu | China | N/A | N/A | N/A | N/A | 10,000 | N/A | text | Wu (China) Pronunciation Dictionary | |
| 257 | Xiang (China) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 10,000 words | Add Quote | hsn_CHN_PHON | Appen Global | Pronunciation Dictionary | Xiang | China | N/A | N/A | N/A | N/A | 10,000 | N/A | text | Xiang (China) Pronunciation Dictionary | |
| 258 | Zulu (South Africa) Pronunciation Dictionary | Text | ASR, TTS, Language Modelling | N/A | 75,000 words | Add Quote | zul_ZAF_PHON | Appen Global | Pronunciation Dictionary | Zulu | South Africa | N/A | N/A | N/A | N/A | 75,000 | N/A | text | Zulu (South Africa) Pronunciation Dictionary |
Use Cases
Whether you are working on a text-to-speech system, a voice recognition system or another solution that relies on natural language, high-quality licensed speech and language datasets allow you to go to market faster and reach more potential customers.
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