The effect of language models on phonetic decoding for spoken term detection
Data(s) |
2009
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Resumo |
Spoken term detection (STD) popularly involves performing word or sub-word level speech recognition and indexing the result. This work challenges the assumption that improved speech recognition accuracy implies better indexing for STD. Using an index derived from phone lattices, this paper examines the effect of language model selection on the relationship between phone recognition accuracy and STD accuracy. Results suggest that language models usually improve phone recognition accuracy but their inclusion does not always translate to improved STD accuracy. The findings suggest that using phone recognition accuracy to measure the quality of an STD index can be problematic, and highlight the need for an alternative that is more closely aligned with the goals of the specific detection task. |
Formato |
application/pdf |
Identificador | |
Publicador |
ACM Multimedia Workshop |
Relação |
http://eprints.qut.edu.au/29644/1/c29644.pdf http://ict.ewi.tudelft.nl/SSCS2009/ Wallace, Roy G., Baker, Brendan J., Vogt, Robert J., & Sridharan, Sridha (2009) The effect of language models on phonetic decoding for spoken term detection. In Proceedings of Searching Spontaneous Conversational Speech (SSCS) ACM Multimedia Workshop, ACM Multimedia Workshop, Beijing, pp. 31-36. |
Direitos |
Copyright 2009 [please consult the authors] |
Fonte |
Faculty of Built Environment and Engineering; Information Security Institute; School of Engineering Systems |
Palavras-Chave | #080107 Natural Language Processing #spoken term detection #phoneme recognition #phoneme lattice #language modelling |
Tipo |
Conference Paper |