Building Features from Audio for Machine Learning

Jyotika Singh

Jyotika Singh

icon-location R1
icon-language English talk
icon-datetime Day 2 • 10:00-10:30
icon-level Intermediate
icon-category Machine Learning


    Audio signals are a different type of data than the more commonly seen types, such as text, numbers and images. Thus, numerical feature extraction for audio data is different and follows processes that try to replicate how human ears perceive sound. Audio and speech processing has a massive amount of research and methods available in MATLAB. Given the popularity of Python in the field of Machine Learning, feature extraction and audio classification model building in Python will be discussed. This talk will cover details about Audio signals, feature types, feature extraction using Python, open-source tools, followed by practical examples of training Machine Learning models using Audio data.



    Jyotika Singh

    Jyotika Singh is the VP of Data Science at ICX Media where mentors and manages her team as they work on NLP, feature engineering, supervised & unsupervised machine learning, research, analytics, programming in Python and distributed computing with Spark. She earned her Master’s in Science from the UCLA where she researched signal & speech processing, developed novel approaches to remove noise from speech and worked on a variety of machine learning on image, text, social media, consumer & entertainment data. She enjoys working on problem solving techniques on text, audio & image, and has opened multiple open-source projects to share her work with the Python & Data Science community. She is passionate about women in STEM and continues mentorship efforts to support the topic. She volunteers as a mentor at Data Science Nigeria and Women Impact Tech.