Cepstral Domain Feature Extraction Utilizing Entropic Distance-Based Filterbank

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概要

• 論文の詳細を見る

• The selection of effective features is especially important in achieving highly accurate speech recognition. Although the mel-cepstrum is a popular and effective feature for speech recognition, it is still unclear that the filterbank adopted in the mel-cepstrum always produces the optimal performance regardless of the phonetic environment of any specific speech recognition task. In this paper, we propose a new cepstral domain feature extraction approach utilizing the entropic distance-based filterbank for highly accurate speech recognition. Experimental results showed that the cepstral features employing the proposed filterbank reduce the relative error by 31% for clean as well as noisy speech compared to the mel-cepstral features.

• （社）電子情報通信学会の論文
• 2010-02-01

著者

• Kim Hoirin

  Department Of Electrical Engineering Korea Advanced Institute Of Science And Technology

• Suh Youngjoo

  Department Of Information And Communications Engineering Korea Advanced Institute Of Science And Tec

関連論文

• Cepstral Domain Feature Extraction Utilizing Entropic Distance-Based Filterbank

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