Analysis on the importance of short-term speech parameterizations for emotional statistical parametric speech synthesis

Ranniery Maia, Masami Akamine

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

This paper presents a study on the importance of shortterm spectral and excitation parameterizations for emotional hidden Markov model (HMM)-based speech synthesis. The analysis is performed through an emotion classification task by using two methods: K-means emotion clustering and Gaussian Mixture Models (GMMs)-based emotion identification. Two known forms of parameterization for the short-term speech spectral envelope, the mel-cepstrum and the mel-line spectrum pairs are utilized while features derived from the complex cepstrum and group delay, and band-aperiodicity coefficients are used as excitation parameters. The emotion-dependent features according to the classification performance are then selected to train emotion-dependent HMM-based synthesizers. Listening tests are performed to verify the impact of the parameters on the similarity of the synthesized speech with its natural version.

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1630-1633
ページ数4
出版ステータスPublished - 2012 12 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 92012 9 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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