Customer data is often at the heart of any project start. But whereas textual and image data are typically easier to collect and label, audio data is often more scarce and tricky.

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This typically results in a few rounds of “back and forth” at a project start with typical questions such as:

How much audio data do you need
How much of that should be labelled
How should we label the audio data
Etc.
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In this internship, we aim to answer those questions to as specific a degree as possible. For this, you will focus on creating a speech transcription engine that can identify and accurately transcribe your colleagues in various contexts. In this process, you’ll identify key relationships between data quantity, quality, type and model accuracy. You’ll then package all of this into a demo which can take various forms for your fellow agents and the world to use!