Speech recognition has made ground-breaking progress in the last few years, thanks to the growing availability of faster hardware, bigger data, and better algorithms. Today real-time, near human-level speech recognition is available on desktop and mobile devices, and leveraging this technology to build your own speech-enabled applications is easier than ever before. Many open source tools for speech, including state-of-the-art libraries like CMUSphinx and kaldi offer powerful APIs for developers to perform live speech recognition. In this talk we will show you how to train a language model and build a custom voice-control interface from scratch using open source tools and real-world data. We will demonstrate a plugin built at JetBrains for controlling your IDE by voice, and give you advice for implementing your own speech applications. No prior experience is necessary.
Since graduating in CS four years ago, I have worked as a data analyst, software engineer, and developer advocate studying machine learning and building developer tools. I enjoy traveling and playing badminton.