DocumentCode :
2021602
Title :
Speech segmentation and clustering based on speaker features
Author :
Sugiyama, M. ; Murakami, J. ; Watanabe, H.
Author_Institution :
ATR Interpreting Telephony Res. Lab., Soraku-gun, Kyoto, Japan
Volume :
2
fYear :
1993
fDate :
27-30 April 1993
Firstpage :
395
Abstract :
The authors describe speech segmentation and clustering algorithms based on speaker features, where speakers, the number of speakers, and speech context are unknown. Several problems are formulated and their solutions are proposed. As in the simpler case, when speech segmentations are known, the output probability clustering algorithm is proposed. In the case of unknown segmentation, an ergodic HMM (hidden Markov model)-based technique is applicable. Both cases are evaluated using simulated multispeaker dialogue speech data.<>
Keywords :
feature extraction; hidden Markov models; speech recognition; clustering algorithms; ergodic HMM; hidden Markov model; output probability clustering algorithm; simulated multispeaker dialogue speech; speaker features; speech segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on
Conference_Location :
Minneapolis, MN, USA
ISSN :
1520-6149
Print_ISBN :
0-7803-7402-9
Type :
conf
DOI :
10.1109/ICASSP.1993.319322
Filename :
319322
Link To Document :
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