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