Human-Centered AI for Disordered Speech Recognition - Katarzyna Foremniak

We talked about: 00:00 DataTalks.Club intro 08:06 Background and career journey of Katarzyna 09:06 Transition from linguistics to computational linguistics 11:38 Merging linguistics and computer science 15:25 Understanding phonetics and morpho-syntax 17:28 Exploring morpho-syntax and its relation to grammar 20:33 Connection between phonetics and speech disorders 24:41 Improvement of voice recognition systems 27:31 Overview of speech recognition technology 30:24 Challenges of ASR systems with atypical speech 30:53 Strategies for improving recognition of disordered speech 37:07 Data augmentation for training models 40:17 Transfer learning in speech recognition 42:18 Challenges of collecting data for various speech disorders 44:31 Stammering and its connection to fluency issues 45:16 Polish consonant combinations and pronunciation challenges 46:17 Use of Amazon Transcribe for generating podcast transcripts 47:28 Role of language models in speech recognition 49:19 Contextual understanding in speech recognition 51:27 How voice recognition systems analyze utterances 54:05 Personalization of ASR models for individuals 56:25 Language disorders and their impact on communication 58:00 Applications of speech recognition technology 1:00:34 Challenges of personalized and universal models 1:01:23 Voice recognition in automotive applications 1:03:27 Humorous voice recognition failures in cars 1:04:13 Closing remarks and reflections on the discussion About the speaker: Katarzyna is a computational linguist with over 10 years of experience in NLP and speech recognition. She has developed language models for automotive brands like Audi and Porsche and specializes in phonetics, morpho-syntax, and sentiment analysis. Kasia also teaches at the University of Warsaw and is passionate about human-centered AI and multilingual NLP. Join our slack: https://datatalks.club/slack.html