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

Akitoshi KATAOKA  Sachiko KURIHARA  Shinji HAYASHI  Takehiro MORIYA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E79-D   No.2   pp.123-129
Publication Date: 1996/02/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Speech Processing and Acoustics
Keyword: 
CELP coding,  conjugae fixed codebook,  trained sparse codebook,  speech quality in a noisy environment,  

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Summary: 
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.