Presentations

Mar 16, 2020

Evaluation of Language Model for Spontaneous Speech Recognition Trained Using Written Language-to-Spoken Language Text Conversion

日本音響学会研究発表会講演論文集
  • Yuya Obashi
  • ,
  • Nishimura Ryota
  • ,
  • Kitaoka Norihide

Language
Japanese
Presentation type

We converted a written text corpus to a spoken text corpus using a sequence-to-sequence model and trained a spoken language model. Although the accuracy of the conversion from written to spoken text was not very high, the learned language models were useful for spoken-speech recognition, as they captured the statistical characteristics of spoken words well. We also investigated what kind of spoken language features this language model is effective for. The results show that the present study is very effective for the insertion of filler words and spoken word-specific endings, and is also effective to some extent for colloquial expressions such as particle omissions.

Link information
URL
https://web.db.tokushima-u.ac.jp/cgi-bin/edb_browse?EID=370068