ORGANIZATION OF SPEAKER SPACE BASED ON VECTOR QUANTIZATION METHOD.

Katsuhiko Shirai; Kazunori Mano; Shunichi Ishige; Koji Sano

ORGANIZATION OF SPEAKER SPACE BASED ON VECTOR QUANTIZATION METHOD.

Katsuhiko Shirai, Kazunori Mano, Shunichi Ishige, Koji Sano

研究成果: Conference contribution

抄録

A method is discussed for characterizing speaker individuality that could be used for speaker adaptation for speaker-independent phoneme recognition. To represent the individual traits of speakers, a speaker space is organized using distributions in a vector-quantized space. This space includes 200 speakers, each shown as a point in it. The experimental results for 200-speaker identification with 10 input words shows performance rates of 82% in first-order and 90% in the second-order case.

本文言語	English
ホスト出版物のタイトル	Proceedings - International Conference on Pattern Recognition
出版社	IEEE
ページ	1152-1154
ページ数	3
ISBN（印刷版）	0818607424
出版ステータス	Published - 1986 12月 1
外部発表	はい

出版物シリーズ

名前	Proceedings - International Conference on Pattern Recognition

ASJC Scopus subject areas

コンピュータビジョンおよびパターン認識

他のファイルとリンク

引用スタイル

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author = "Katsuhiko Shirai and Kazunori Mano and Shunichi Ishige and Koji Sano",

year = "1986",

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AU - Shirai, Katsuhiko

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AU - Ishige, Shunichi

AU - Sano, Koji

PY - 1986/12/1

Y1 - 1986/12/1

N2 - A method is discussed for characterizing speaker individuality that could be used for speaker adaptation for speaker-independent phoneme recognition. To represent the individual traits of speakers, a speaker space is organized using distributions in a vector-quantized space. This space includes 200 speakers, each shown as a point in it. The experimental results for 200-speaker identification with 10 input words shows performance rates of 82% in first-order and 90% in the second-order case.

AB - A method is discussed for characterizing speaker individuality that could be used for speaker adaptation for speaker-independent phoneme recognition. To represent the individual traits of speakers, a speaker space is organized using distributions in a vector-quantized space. This space includes 200 speakers, each shown as a point in it. The experimental results for 200-speaker identification with 10 input words shows performance rates of 82% in first-order and 90% in the second-order case.

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M3 - Conference contribution

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T3 - Proceedings - International Conference on Pattern Recognition

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BT - Proceedings - International Conference on Pattern Recognition

PB - IEEE

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ORGANIZATION OF SPEAKER SPACE BASED ON VECTOR QUANTIZATION METHOD.

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出版物シリーズ

ASJC Scopus subject areas

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