The aim of our paper is to study the interest of part of speech (POS) tagging to improve speech recognition. We first evaluate the part of misrecognized words that can be corrected using POS information; the analysis of a short extract of French radio broadcast news shows that an absolute decrease of the word error rate by 1.1% can be expected. We also demonstrate quantitatively that traditional POS taggers are reliable when applied to spoken corpus, including automatic transcriptions. This new result enables us to effectively use POS tag knowledge to improve, in a postprocessing stage, the quality of transcriptions, especially correcting agreement errors. © Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Huet, S., Gravier, G., & Sébillot, P. (2006). Are morphosyntactic taggers suitable to improve automatic transcription? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4188 LNCS, pp. 391–398). Springer Verlag. https://doi.org/10.1007/11846406_49
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