Illustration of the interior of a concept car

Blog Home Industry Insights   •   May 21, 2019

How a Tier 1 Automotive Software Provider Creates Smarter, More Natural In-Car Infotainment Systems

The Company

A leading provider of vehicle electronics software approached Appen to collect audio and linguistic data to help develop automatic speech recognition (ASR) capabilities for its in-car infotainment system.

The Situation

For an in-car infotainment system — or any ASR system — to recognize and correctly process voice commands, it must be trained on speech data that accounts for a broad range of inputs and all possible variation in how people speak. There are countless different verbal commands a driver might use to adjust the climate control, radio, navigation, phone, and other settings in an automobile. Training these systems to understand multiple dialects and various speaker categories poses an even bigger challenge, requiring many thousands of utterances in each of the targeted languages.

The Solution

Appen provides services to collect natural language data and text data, covering all the scenarios and variation that the system might encounter in the real world. Working with in-market, on-demand crowds of native speakers, Appen is able to rapidly expand ASR capabilities in new locations and languages, for any given scenario. And because the company has strict standards for audio recording quality, Appen replicates the same advanced recording procedures across different locations and studios, and supervises them to comply with quality standards for a range of languages used in the automotive industry.

Services included:

  • Spontaneous, unscripted speech data collection in which native speakers are given a set of scenarios (i.e., How do you ask for temp lowered? Put your favorite music on? Change the radio station?), and must generate various responses
  • Text data collection using similar scenarios as for speech, but aimed to obtain larger volumes of data and a broader variety of speakers
  • Scripted speech data collection for short, fixed utterances
  • Test driving simulation to mimic the cognitive load of driving, so speakers come up with more natural, real-world responses
  • Country-specific studio data collection with specialist equipment to ensure that different studios are calibrated for precision and compliance to strict audio standards

The Outcome

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