Combining multiple high quality corpora for improving HMM-TTS

Vincent Wan, Javier Latorre, K. K. Chin, Langzhou Chen, Mark J.F. Gales, Heiga Zen, Kate Knill, Masami Akamine

研究成果: Conference contribution

20 被引用数 (Scopus)

抄録

The most reliable way to build synthetic voices for end-products is to start with high quality recordings from professional voice talents. This paper describes the application of average voice models (AVMs) and a novel application of cluster adaptive training (CAT) to combine a small number of these high quality corpora to make best use of them and improve overall voice quality in hidden Markov model based text-to-speech (HMMTTS) systems. It is shown that integrated training by both CAT and AVM approaches, yields better sounding voices than speaker dependent modelling. It is also shown that CAT has an advantage over AVMs when adapting to a new speaker. Given a limited amount of adaptation data CATmaintains a much higher voice quality even when adapted to tiny amounts of speech.

本文言語English
ホスト出版物のタイトル13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012
ページ1134-1137
ページ数4
出版ステータスPublished - 2012 12月 1
外部発表はい
イベント13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012 - Portland, OR, United States
継続期間: 2012 9月 92012 9月 13

出版物シリーズ

名前13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012
2

Conference

Conference13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012
国/地域United States
CityPortland, OR
Period12/9/912/9/13

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 通信

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