Computationally Efficient Cepstral Domain Feature Compensation
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概要
- 論文の詳細を見る
In this letter, we propose a novel approach to feature compensation performed in the cepstral domain. Processing in the cepstral domain has the advantage that the spectral correlation among different frequencies is taken into consideration. By introducing a linear approximation with diagonal covariance assumption, we modify the conventional log-spectral domain feature compensation technique to fit to the cepstral domain. The proposed approach shows significant improvements in the AURORA2 speech recognition task.
- （社）電子情報通信学会の論文
- 2009-01-01
著者
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KIM Nam
School of Electrical and Computer Engineering, Chungbuk National University
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Han Chang
Seoul National Univ. Seoul Kor
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Han Chang
School Of Electrical Engineering And The Institute Of New Media And Communications Seoul National Un
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LIM Woohyung
School of Electrical Engineering and the Institute of New Media and Communications, Seoul National U
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Lim Woohyung
School Of Electrical Engineering And The Institute Of New Media And Communications Seoul National Un
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Kim Nam
School Of Electrical Engineering And The Institute Of New Media And Communications Seoul National Un
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Kim Nam
School Of Electrical And Computer Engineering Chungbuk National University
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Kim Nam
School Of Electrical And Computer Engineering Chungbuk National Univ.
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HAN Chang
School of Electrical Engineering and the INMC, Seoul National University
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