Automatic estimation of dialect mixing ratio for dialect speech recognition

Naoki Hirayama, Koichiro Yoshino, Katsutoshi Itoyama, Shinsuke Mori, Hiroshi G. Okuno

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

This paper proposes methods for determining an appropriate mixing ratio of dialects in automatic speech recognition (ASR) for dialects. To handle ASR for various dialects, it has been re- ported to be effective to train a language model using a dialect- mixed corpus. One reason behind this is geographical continu- ity of spoken dialect; we regard spoken dialect as a mixture of various dialects. This mixing ratio changes at every moment as well as depends on a speaker. We can improve recognition accu- racy by giving an appropriate dialect mixing ratio for a speaker's dialect. The mixing ratio is generally unknown and requires to be estimated and updated referring to input utterances. We han- dle two methods for updating it based on recognition results; one is to compute contribution of dialects for each recognized word, and the other is to predict mixture information referring to a whole recognized sentence based on topic modeling. The experimental result shows that the mixing ratio estimated by these methods realized higher recognition accuracy than a fixed mixing ratio.

本文言語English
ホスト出版物のタイトルProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
出版社International Speech and Communication Association
ページ1492-1496
ページ数5
出版ステータスPublished - 2013
外部発表はい
イベント14th Annual Conference of the International Speech Communication Association, INTERSPEECH 2013 - Lyon, France
継続期間: 2013 8 252013 8 29

Other

Other14th Annual Conference of the International Speech Communication Association, INTERSPEECH 2013
CountryFrance
CityLyon
Period13/8/2513/8/29

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modelling and Simulation

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