Automatic Transcription of Lecture Speech using Language Model Based on Speaking-Style Transformation of Proceeding Texts

摘要

For language modeling of spontaneous speech recognition, we propose a style transformation approach, which transforms written texts to a spoken-style language model. Since these two styles are largely different and thus direct transformation is difficult, we cascade two transformation methods; rule-based transformation to rewrite written-style texts to intermediate "verbatim" texts, and statistical transformation of language model from the verbatim style to the spoken style which is suitable for ASR. In an experimental evaluation on real lecture speech, the proposed transformation approach achieved higher performance than the conventional linear interpolation method.