Audio data is all around us. In this talk, we'll look at ways to use Python and audio-data focused libraries to extract features and train predictions models using audio data.
Data comes in many shapes and sizes. In this session, we’ll look into the process of converting audio files into valuable data. We’ll go over the different types of audio formats and how format and type of audio plays a role in the quality of the outcome. We’ll go over different transcription options available today and provide a demo of converting audio data into text. We’ll review ways of storing and searching text data at scale using open source tools and Natural Language Processing (NLP) techniques. Going further we’ll explore different techniques for building machine learning models on the transcribed text data. You’ll leave this session with a firm understanding of how-to take audio data and convert it into actionable insights.