Spoken Term Detection System Based On Combination Of Lvcsr And Phonetic Search

MLMI'07: Proceedings of the 4th international conference on Machine learning for multimodal interaction(2008)

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摘要
The paper presents the Brno University of Technology (BUT) system for indexing and search of speech, combining LVCSR and phonetic approach. It brings a complete description of individual building blocks of the system from signal processing, through the recognizers, indexing and search until the normalization of detection scores. It also describes the data used in the first edition of NIST Spoken term detection (STD) evaluation. The results are presented on three US-English conditions - meetings, broadcast news and conversational telephone speech, in terms of detection error trade-off (DET) curves and term-weighted values (TWV) metrics defined by NIST.
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关键词
Language Model, Acoustic Model, Inverted Index, Broadcast News, Maximum Likelihood Linear Regression
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