Sixth International Conference on Spoken Language Processing
October 16-20, 2000
Multichannel Signal Separation for Cocktail Party Speech Recognition: A Dynamic Recurrent Network
Seungjin Choi (1), Heonseok Hong (1), Hervé Glotin (2), Frédéric Berthommier (2)
(1) Department of Electrical Engineering, Chungbuk National University, Korea
This paper addresses the method of multichannel signal
separation with its application to cocktail party speech
recognition. First, we present a fundamental principle for
multi-channel signal separation which describes what spatial
independence criterion results in. Second, for practical
implementation of the signal separation filter, we consider a
dynamic recurrent network and develop a new simple learning
algorithm. The performance of the proposed method is
evaluated in terms of word recognition error rate (WER).
Experimental results show that our proposed method
dramatically improves the word recognition performance in the
case of two simultaneous speeches.
(2) ICP, INPG, Grenoble, France
Choi, Seungjin / Hong, Heonseok / Glotin, Hervé / Berthommier, Frédéric (2000):
"Multichannel signal separation for cocktail party speech recognition: a dynamic recurrent network",
In ICSLP-2000, vol.3, 83-86.