Statistical voice conversion using GA-based informative feature

Kohei Sawada, Yoji Tagami, Satoshi Tamura, Masanori Takehara, Satoru Hayamizu

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

In order to make voice conversion (VC) robust to noise, we propose VC using GA-based informative feature (GIF), by adding an extraction process of GIF to a conventional VC. GIF is proposed as a feature that can be applied not only in pattern recognition but also in relative tasks. In speech recognition, furthermore, GIF could improve recognition accuracy in noise environment. We evaluated the performances of VC using spectral segmental features (conventional method) and GIF, respectively. Objective experimental result indicates that in noise environments, the proposed method was better than the conventional method. Subjective experiment was also conducted to compare the performances. These results show that application of GIF to VC was effective.

本文言語English
ホスト出版物のタイトル2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012
出版ステータスPublished - 2012
外部発表はい
イベント2012 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012 - Hollywood, CA, United States
継続期間: 2012 12 32012 12 6

出版物シリーズ

名前2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012

Other

Other2012 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012
国/地域United States
CityHollywood, CA
Period12/12/312/12/6

ASJC Scopus subject areas

  • 情報システム

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