Deep Learning Interpretability and Explainability of Speech in a Clinical Context
Offered By: Center for Language & Speech Processing(CLSP), JHU via YouTube
Course Description
Overview
Explore deep learning interpretability and explainability of speech in a clinical context through this 54-minute conference talk presented by Sondes ABDERRAZEK from the Center for Language & Speech Processing (CLSP) at Johns Hopkins University. Delivered as part of the JSALT 2023 workshop held in Le Mans, France, this presentation delves into the crucial aspects of understanding and explaining deep learning models applied to speech analysis in healthcare settings. Gain insights into the challenges and opportunities of interpreting complex neural networks used for speech processing in clinical applications. Learn about cutting-edge techniques for making these models more transparent and accountable, enhancing their potential for improving patient care and medical diagnostics through speech analysis.
Syllabus
Deep learning interpretability and explainability of speech in a clinical context -Sondes ABDERRAZEK
Taught by
Center for Language & Speech Processing(CLSP), JHU
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent