“Appen’s platform is really easy to use. What makes it great is you can reach so many different channels because of its global outreach.” – Kenneth Benoit, Director of the Data Science Institute, LSE The University Founded in 1895, the London School of Economics and Political Science (LSE) has long been a global leader in social sciences among universities. One of …
Appen is so fast. Using their platform, we could do overnight what used to take us a month. Appen is wonderfully efficient. – Rick Britt, Vice President of AI, CallMiner The Company Founded in 2002, CallMiner is the pioneer of the artificial intelligence (AI)-powered speech analytics space. In the years since, the company has continued to advance its AI software …
We were expanding to a new market. Although we had a fully localized software, we were lacking resources, so our clients could not optimally use it. Appen helped us out with French lexicon data. – Ines Wendler, Product Manager, MediaInterface The Company For over 20 years, MediaInterface has delivered language technology solutions to primarily healthcare-related institutions in Germany and other …
We were able to quickly go through different iterations of annotation tasks with our crowd workers and understand what was working and what wasn’t. The fact that the quality control features are already built into the Appen platform makes task setup even easier. – Madeleine van Zuylen, Data Science Analyst, Allen Institute for AI The Company The Allen Institute for …
The Company A social media company needed large amounts of training data to improve its tool to better understand user-generated messages by identifying user intent, sentiment, and entities (people, places, events) from natural language. The Challenge A leading social media company needed a large amount of data to improve its machine learning model. This would allow its tool to better …
The Company A leading multinational technology company teamed up with us to help develop an automatic speech recognition (ASR) system designed from the ground up to specifically cater to children’s applications. The Challenge You might not be surprised to learn that most speech recognition systems are designed with adult speakers in mind. To date, the nuances and idiosyncrasies of …
The Company A leading global OEM has worked with us for over 10 years to develop the data needed to train its voice recognition systems for more than 20 languages. The Challenge With the proliferation of mobile devices and increasing consumer expectations to stay connected regardless of their environment, automotive makers are under growing pressure to deliver on the promise …
2020 Predictions in Artificial Intelligence to Consider When Operationalizing AI Developments With 2019 hardly fading in the rear-view mirror, it’s a good time to take a step back and see what’s in store for the next 12 months. For those managing and implementing AI and ML projects and deployments, it’s been a rapidly evolving ecosystem, and 2020 will be no …
Chatbots and their more sophisticated counterparts, virtual assistants, have emerged as a key tool to streamline customer service operations for organizations in a wide range of industries, and to help reduce costs.
When planning the development of a chatbot or virtual assistant, it’s important to begin the conversational design process with a clear data strategy in place. Conversational design requires more than just an understanding of the fundamentals of voice user interface design — you also need to understand how to solve some of the key challenges in data preparation. Working with the …
The Company A leading provider of vehicle electronics software approached us to collect audio and linguistic data to help develop automatic speech recognition (ASR) capabilities for its in-car infotainment system. The Challenge For an in-car infotainment system — or any automatic speech recognition system — to recognize and correctly process voice commands, it must be trained on speech data that accounts for …
The unstoppable march of Artificial Intelligence (AI) and machine learning is already touching our lives in so many ways. But its effects have only just begun to take hold.
Prithivi Pradeep, Appen VP of Business Development, and I recently attended Conversational Interaction in San Jose, CA. The conference provides companies and individuals a great opportunity to share and learn about the resources and knowledge that allow them to embrace AI. The importance of Artificial Intelligence technology has been emphasized by influential corporate executives and thoughtful analysts alike. Conversational interfaces are a major …
When designing a voice recognition system, it’s important that the speech system understands everyone speaking to it. But what happens when a speech recognition system doesn’t account for children’s speech? Most speech recognition platforms are only designed with adults in mind. Child speech is very different than adult speech, and not all speech recognition devices are well-equipped to deal with …
A leading social media company needed large amounts of data to improve machine learning. Appen helped them secure the data needed to enhance the model. Read more.
Appen to present research on speech recognition, speaker comparisons, and Pashto speech data at this year’s Interspeech conference.
While every enterprise has a Big Data strategy, few have an Natural Language Processing (NLP) data strategy. Do you?
How can we improve voice activated devices’ abilities to better understand and communicate with us? Human speech data, terabytes of it.
While the concept of AI is not new, the technology is experiencing a rebirth in the form of machine learning and cognitive computing.
