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Committee Date Time Place Paper Title / Authors Abstract Paper #
EA 2022-05-13
13:10		 Online Online Fast Blind Source Separation in Noisy Reverberant Environments Using Independent Vector Extraction
Rintaro Ikeshita, Tomohiro Nakatani (NTT) EA2022-5		 Blind source separation (BSS) is a technique of separating and extracting individual source signals only from their mixt... [more] EA2022-5
pp.20-25
SP 2017-08-30
11:00		 Kyoto Kyoto Univ. [Poster Presentation] Semi-blind speech separation and enhancement using recurrent neural network
Masaya Wake, Yoshiaki Bando, Masato Mimura, Katsutoshi Itoyama, Kazuyoshi Yoshii, Tatsuya Kawahara (Kyoto Univ.) SP2017-22		 This paper describes a semi-blind speech enhancement method using a neural network.
In a human-robot speech interaction... [more]		 SP2017-22
pp.13-18
SIP, EA, SP 2015-03-02
09:50		 Okinawa   Unified approach for BSS, DOA estimation, audio event detection and dereverberation with multichannel factorial HMM and DOA mixture model
Takuya Higuchi (Univ. of Tokyo), Hirokazu Kameoka (Univ. of Tokyo/ NTT) EA2014-74 SIP2014-115 SP2014-137		 We deal with the problems of blind source separation, dereverberation, audio event detection and DOA estimation. We prev... [more] EA2014-74 SIP2014-115 SP2014-137
pp.13-18
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