Session Video
An Overview of Modern Speech Recognition
Abstract
Automatic speech recognition has been impacted by advances in related fields like image processing and natural language processing in recent years. One notable achievement in these areas has been the use of self-supervised learning to improve performance in computer vision and NLP tasks. This led to the development of the first self-supervised language model for speech representations, which has demonstrated impressive results in various NLP tasks. In this talk, we will review the key principles of automatic speech recognition and discuss the current progress, research, and challenges in the field
Speaker
- Gal Hever
- Algorithm Developer, Vision Map
- MSc in Data Science, with over a decade of accumulated expertise in Machine Learning & Data Analytics from 8200, academy, and industry. Deploying algorithms to production by applying data-driven Machine Learning & AI solutions end to end, starting from research to development and testing.
Slides
I’ve read a couple of books on the subject, but this shows more up to date results.
Show me the papers?
The Data Nights course should be worth taking
Citation
@online{bochman2016,
author = {Bochman, Oren},
title = {An {Overview} of {Modern} {Speech} {Recognition}},
date = {2016-11-01},
url = {https://orenbochman.github.io/posts/2023/01-11-nlp-il-meetup-intuit/talk3.html},
langid = {en}
}