A Statistical Approach to Error Compensation in Spectral Quantization

Seung Ho CHOI; Hong Kook KIM

doi:10.1093/ietisy/e90-d.9.1460

A Statistical Approach to Error Compensation in Spectral Quantization

Seung Ho CHOI, Hong Kook KIM

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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.

Publication: IEICE TRANSACTIONS on Information Vol.E90-D No.9 pp.1460-1464

Publication Date: 2007/09/01

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Online ISSN: 1745-1361

DOI: 10.1093/ietisy/e90-d.9.1460

Type of Manuscript: LETTER

Category: Speech and Hearing

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Seung Ho CHOI, Hong Kook KIM, "A Statistical Approach to Error Compensation in Spectral Quantization" in IEICE TRANSACTIONS on Information, vol. E90-D, no. 9, pp. 1460-1464, September 2007, doi: 10.1093/ietisy/e90-d.9.1460.
Abstract: 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.
URL: https://globals.ieice.org/en_transactions/information/10.1093/ietisy/e90-d.9.1460/_p

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@ARTICLE{e90-d_9_1460,
author={Seung Ho CHOI, Hong Kook KIM, },
journal={IEICE TRANSACTIONS on Information},
title={A Statistical Approach to Error Compensation in Spectral Quantization},
year={2007},
volume={E90-D},
number={9},
pages={1460-1464},
abstract={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.},
keywords={},
doi={10.1093/ietisy/e90-d.9.1460},
ISSN={1745-1361},
month={September},}

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TY - JOUR
TI - A Statistical Approach to Error Compensation in Spectral Quantization
T2 - IEICE TRANSACTIONS on Information
SP - 1460
EP - 1464
AU - Seung Ho CHOI
AU - Hong Kook KIM
PY - 2007
DO - 10.1093/ietisy/e90-d.9.1460
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E90-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2007
AB - 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.
ER -