Presentation 1996/2/23
Robust Entropy Coded Vector Quantization with Hidden Markov Models
Tadashi Yonezaki, Kiyohiro Shikano,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) We propopse a new speech coding approach, which consists of Hidden Markov Models(HMMs) and entropy coding scheme. The entropy coding system is determined depending on the speech status modeled by HMMs, so the proposing approach can adaptively allocate suitable numbers of bits to the codewords. This approach realizes about 0.3[dB] coding gain in cepstrum distance(8 states HMMs). In other words, 8 bit-codebook is represented by about 6.5 bits for average code length. We also research for robustness to the channel error. HMMs and the entropy coding system, which seem to be weak to the channel error, are augmented to be robust, so that the influence of the channel error is decreased into one-forth.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Speech Coding / Vector Quantization / HMMs / Entropy Coding / Robustness
Paper # SP95-131
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Conference Information
Committee SP
Conference Date 1996/2/23(1days)
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Registration To Speech (SP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Robust Entropy Coded Vector Quantization with Hidden Markov Models
Sub Title (in English)
Keyword(1) Speech Coding
Keyword(2) Vector Quantization
Keyword(3) HMMs
Keyword(4) Entropy Coding
Keyword(5) Robustness
1st Author's Name Tadashi Yonezaki
1st Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology, NAIST.()
2nd Author's Name Kiyohiro Shikano
2nd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology, NAIST.
Date 1996/2/23
Paper # SP95-131
Volume (vol) vol.95
Number (no) 534
Page pp.pp.-
#Pages 8
Date of Issue