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Title: Audio-visual Speech Enhancement and Separation Based on Deep Learning
Date: 17 November 2022
Time: 1:00 PM Eastern (New York time)
Duration: Approximately 1 Hour
Presenters: Dr. Daniel Michelsanti
Based on the IEEE Xplore® article: An Overview of Deep-Learning-Based Audio-Visual Speech Enhancement and Separation
Published: IEEE/ACM Transactions on Audio, Speech, and Language Processing, March 2021, available in IEEE Xplore®
Dr. Daniel Michelsanti (S'16 M'21) received the B.Sc. degree in computer science and electronic engineering (cum laude) at the University of Perugia, Italy, and the M.Sc. degree in vision, graphics and interactive systems at Aalborg University, Denmark, in 2014 and 2017, respectively. He also received his PhD degree from Aalborg University, Denmark, in 2021, where he investigated the problem of audio-visual speech enhancement using deep learning.
He was then employed as a research assistant at the section for Artificial Intelligence and Sound (AIS), Department of Electronic Systems, Aalborg University, Denmark, where he conducted research on acoustic signal analysis for industry 4.0. Currently, he is an industrial postdoctoral researcher at Oticon and Aalborg University.
Dr. Michelsanti’s research interests are in the areas of speech enhancement, computer vision and machine learning, specifically deep learning.
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