Imperial College London > Talks@ee.imperial > COMMSP Seminar > Blind Source Separation for Real-World Speech Applications

Blind Source Separation for Real-World Speech Applications

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In this talk, I review blind source separation technology and its recent current. Blind source separation (BSS) is an approach taken to estimate original source signals using only observed signals without knowing a priori information. Owing to the attractive feature of BSS , much attention has been paid to BSS in many fields of signal processing. In this talk, first, the basic principle of speech/acoustic signal separation based on independent component analysis is explained, and the recent research and development trends are shown. Next, we can demonstrate our recently developed real-time BSS unit which is one of the world’s smallest BSS microphone miniaturized into pocket-size hardware. Finally, we show a hands-free spoken dialogue system with real-time BSS used for real-world speech applications.

Biography: Hiroshi Saruwatari received the B.E., M.E. and Ph.D. degrees in electrical engineering from Nagoya University, Japan, in 1991, 1993 and 2000, respectively. He is currently an associate professor of Nara Institute of Science and Technology, Japan. His research interests include noise-robust speech processing, array signal processing and BSS . He received paper awards from IEICE in 2001 and 2006, from TAF in 2004 and 2009, and from IEEE -IROS2005 in 2006. He won the first prize in IEEE MLSP2007 Data Analysis Competition for BSS .

This talk is part of the COMMSP Seminar series.

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