Statistical Voice Conversion using GA-based Informative Feature

被引：0

作者：

Sawada, Kohei ^{[1
]}

Tagami, Yoji ^{[1
]}

Tamura, Satoshi ^{[1
]}

Takehara, Masanori ^{[1
]}

Hayamizu, Satoru ^{[1
]}

机构：

[1] Gifu Univ, Dept Informat Sci, Gifu, Japan

来源：

2012 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC) | 2012年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页数：4

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