Deep Learning Interpretability and Explainability of Speech in a Clinical Context

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.