|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
SEGMENT GENERATION AND CLUSTERING IN THE HTK BROADCAST NEWS TRANSCRIPTION SYSTEM
T. Hain, S.E. Johnson, A. Tuerk, P.C. Woodland & S.J. Young
This paper describes the segmentation, gender detection and segment clustering scheme used in the 1997 HTK broadcast news evaluation system and presents results on both the unpartitioned 1996 development and the 1997 evaluation sets. The stages of our approach are presented, namely classification, segmentation and gender detection, gender relabelling, and clustering of speech segments. The evaluation audio stream has been segmented according to audio type with a frame accuracy up to 95%. Further segmentation and gender labelling gave up to 99% frame accuracy with 127 multiple speaker segments. Experiments using two different segmentation approaches and three clustering schemes are presented.
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2005 Cambridge University Engineering Dept
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