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Deep Learning Interpretability and Explainability of Speech in a Clinical Context

Offered By: Center for Language & Speech Processing(CLSP), JHU via YouTube

Tags

Deep Learning Courses Artificial Intelligence Courses Machine Learning Courses Speech Recognition Courses Speech Analysis Courses Interpretability Courses

Course Description

Overview

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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

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