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Spoken Term Detection System Based on Combination of LVCSR and Phonetic Search

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Book cover Machine Learning for Multimodal Interaction (MLMI 2007)

Abstract

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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References

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Andrei Popescu-Belis Steve Renals Hervé Bourlard

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© 2008 Springer-Verlag Berlin Heidelberg

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Szöke, I. et al. (2008). Spoken Term Detection System Based on Combination of LVCSR and Phonetic Search. In: Popescu-Belis, A., Renals, S., Bourlard, H. (eds) Machine Learning for Multimodal Interaction. MLMI 2007. Lecture Notes in Computer Science, vol 4892. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78155-4_21

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  • DOI: https://doi.org/10.1007/978-3-540-78155-4_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78154-7

  • Online ISBN: 978-3-540-78155-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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