A Statistical Approach to Error Compensation in Spectral Quantization(Speech and Hearing)
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概要
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In this paper, we propose a statistical approach to improve the performance of spectral quantization of speech coders. The proposed techniques compensate for the distortion in a decoded line spectrum pair (LSP) vector based on a statistical mapping function between a decoded LSP vector and its corresponding original LSP vector. We first develop two codebook-based probabilistic matching (CBPM) methods by investigating the distribution of LSP vectors. In addition, we propose an iterative procedure for the two CBPMs. Next, the proposed techniques are applied to the predictive vector quantizer (PVQ) used for the IS-641 speech coder. The experimental results show that the proposed techniques reduce average spectral distortion by around 0.064 dB and the percentage of outliers compared with the PVQ without any compensation, resulting in transparent quality of spectral quantization. Finally, the comparison of speech quality using the perceptual evaluation of speech quality (PESQ) measure is performed and it is shown that the IS-641 speech coder employing the proposed techniques has better decoded speech quality than the standard IS-641 speech coder.
- 2007-09-01
著者
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KIM Hong
School of Information and Communications, Gwangju Institute of Science and Technology (GIST)
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Kim Hong
Department Of Chemistry Advanced Materials Chemistry Research Center Korea University
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Kim Hong
Gwangju Inst. Sci. And Technol. Gwangju Kor
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Kim Hong
Dept. Of Information And Communications Gwangju Institute Of Science And Technology
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Choi Seung
Department Of Applied Chemistry Konkuk University
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Choi Seung
Department Of Electronic And Information Engineering Seoul National University Of Technology
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Kim Hong
Department of Applied Sciences, Korea Maritime University, Busan 606-791, Korea
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