Improved CELP-Based Coding in a Noisy Environment Using a Trained Sparse Conjugate Codebook

Akitoshi KATAOKA; Sachiko KURIHARA; Shinji HAYASHI; Takehiro MORIYA

Improved CELP-Based Coding in a Noisy Environment Using a Trained Sparse Conjugate Codebook

Akitoshi KATAOKA, Sachiko KURIHARA, Shinji HAYASHI, Takehiro MORIYA

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A trained sparse conjugate codebook is proposed for improving the speech quality of CELP-based coding in a noisy environment. Although CELP coding provides high quality at a low bit rate in a silent environment (creating clean speech), it cannot provide a satisfactory quality in a noisy environment because the conventional fixed codebook is designed to be suitable for clean speech. The proposed codebook consists of two sub-codebooks; each sub-codebook consists of a random component and a trained component. Each component has excitation vectors consisting of a few pulses. In the random component, pulse position and amplitude are determined randomly. Since the radom component does not depend on the speech characteristics, it handles noise better than the trained one. The trained component maintains high quality for clean speech. Since excitation vector is the sum of the two sub-excitation vectors, this codebook handles various speech conditions by selecting a sub-vector from each component. This codebook also reduces the computational complexity of a fixed codebook search and memory requirements compared with the conventional codebook. Subjective testing (absolute category rating (ACR) and degradation category rating (DCR)) indicated that this codebook improves speech quality compared with the conventional trained codebook for noisy speech. The ACR test showed that the quality of the 8 kbit/s CELP coder with this codebook is equivalent to that of the 32 kbit/s ADPCM for clean speech.

Publication: IEICE TRANSACTIONS on Information Vol.E79-D No.2 pp.123-129

Publication Date: 1996/02/25

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Type of Manuscript: PAPER

Category: Speech Processing and Acoustics

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Akitoshi KATAOKA, Sachiko KURIHARA, Shinji HAYASHI, Takehiro MORIYA, "Improved CELP-Based Coding in a Noisy Environment Using a Trained Sparse Conjugate Codebook" in IEICE TRANSACTIONS on Information, vol. E79-D, no. 2, pp. 123-129, February 1996, doi: .
Abstract: A trained sparse conjugate codebook is proposed for improving the speech quality of CELP-based coding in a noisy environment. Although CELP coding provides high quality at a low bit rate in a silent environment (creating clean speech), it cannot provide a satisfactory quality in a noisy environment because the conventional fixed codebook is designed to be suitable for clean speech. The proposed codebook consists of two sub-codebooks; each sub-codebook consists of a random component and a trained component. Each component has excitation vectors consisting of a few pulses. In the random component, pulse position and amplitude are determined randomly. Since the radom component does not depend on the speech characteristics, it handles noise better than the trained one. The trained component maintains high quality for clean speech. Since excitation vector is the sum of the two sub-excitation vectors, this codebook handles various speech conditions by selecting a sub-vector from each component. This codebook also reduces the computational complexity of a fixed codebook search and memory requirements compared with the conventional codebook. Subjective testing (absolute category rating (ACR) and degradation category rating (DCR)) indicated that this codebook improves speech quality compared with the conventional trained codebook for noisy speech. The ACR test showed that the quality of the 8 kbit/s CELP coder with this codebook is equivalent to that of the 32 kbit/s ADPCM for clean speech.
URL: https://global.ieice.org/en_transactions/information/10.1587/e79-d_2_123/_p

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@ARTICLE{e79-d_2_123,
author={Akitoshi KATAOKA, Sachiko KURIHARA, Shinji HAYASHI, Takehiro MORIYA, },
journal={IEICE TRANSACTIONS on Information},
title={Improved CELP-Based Coding in a Noisy Environment Using a Trained Sparse Conjugate Codebook},
year={1996},
volume={E79-D},
number={2},
pages={123-129},
abstract={A trained sparse conjugate codebook is proposed for improving the speech quality of CELP-based coding in a noisy environment. Although CELP coding provides high quality at a low bit rate in a silent environment (creating clean speech), it cannot provide a satisfactory quality in a noisy environment because the conventional fixed codebook is designed to be suitable for clean speech. The proposed codebook consists of two sub-codebooks; each sub-codebook consists of a random component and a trained component. Each component has excitation vectors consisting of a few pulses. In the random component, pulse position and amplitude are determined randomly. Since the radom component does not depend on the speech characteristics, it handles noise better than the trained one. The trained component maintains high quality for clean speech. Since excitation vector is the sum of the two sub-excitation vectors, this codebook handles various speech conditions by selecting a sub-vector from each component. This codebook also reduces the computational complexity of a fixed codebook search and memory requirements compared with the conventional codebook. Subjective testing (absolute category rating (ACR) and degradation category rating (DCR)) indicated that this codebook improves speech quality compared with the conventional trained codebook for noisy speech. The ACR test showed that the quality of the 8 kbit/s CELP coder with this codebook is equivalent to that of the 32 kbit/s ADPCM for clean speech.},
keywords={},
doi={},
ISSN={},
month={February},}

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TY - JOUR
TI - Improved CELP-Based Coding in a Noisy Environment Using a Trained Sparse Conjugate Codebook
T2 - IEICE TRANSACTIONS on Information
SP - 123
EP - 129
AU - Akitoshi KATAOKA
AU - Sachiko KURIHARA
AU - Shinji HAYASHI
AU - Takehiro MORIYA
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E79-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 1996
AB - A trained sparse conjugate codebook is proposed for improving the speech quality of CELP-based coding in a noisy environment. Although CELP coding provides high quality at a low bit rate in a silent environment (creating clean speech), it cannot provide a satisfactory quality in a noisy environment because the conventional fixed codebook is designed to be suitable for clean speech. The proposed codebook consists of two sub-codebooks; each sub-codebook consists of a random component and a trained component. Each component has excitation vectors consisting of a few pulses. In the random component, pulse position and amplitude are determined randomly. Since the radom component does not depend on the speech characteristics, it handles noise better than the trained one. The trained component maintains high quality for clean speech. Since excitation vector is the sum of the two sub-excitation vectors, this codebook handles various speech conditions by selecting a sub-vector from each component. This codebook also reduces the computational complexity of a fixed codebook search and memory requirements compared with the conventional codebook. Subjective testing (absolute category rating (ACR) and degradation category rating (DCR)) indicated that this codebook improves speech quality compared with the conventional trained codebook for noisy speech. The ACR test showed that the quality of the 8 kbit/s CELP coder with this codebook is equivalent to that of the 32 kbit/s ADPCM for clean speech.
ER -