Machine Learning Signals - Christopher Oates, audEERING

Christopher Oates is a Senior Audio DSP Engineer at audEERING, an audio analysis company that specialises in emotional artificial intelligence. Chris explains how the human voice production system works, and introduces us to a technique called linear predictive coding (LPC) which can extract the features of the voice. We then focus on machine learning for audio, including using expert audio knowledge along with machine learning methods, leveraging the openSMILE toolkit for feature extraction, and signal processing techniques. Chris explains things really well and even brought along some audio clips to help illustrate the signal concepts. He then reveals some of the latest projects at audEERING, including using speech analytics in gaming applications, such as whisper detection in a ninja game! It's an awesome episode that is jam-packed with useful and interesting information. Enjoy! Links from the show: audEERING: https://www.audeering.com/ Chris on compressed audio and ML: http://bit.ly/2MMW7fX Blog on emotional games: http://bit.ly/2MOi0LY Blog on emotion detection: http://bit.ly/2MN0wzj openSMILE: http://bit.ly/2MRgfO8 Video on Intelligent Machines: http://bit.ly/2MNuraK CSO interview: http://bit.ly/2MOq8M8 Sponsors: Dabble Lab: https://youtube.com/dabblelab Find us here: Website Apple Podcasts Spotify YouTube Discord LinkedIn X Reddit Patreon [email protected] ★ Support this podcast on Patreon ★