Presentation | 1997/1/16 High-speed Segment Quantization Based on KL-expansion and Generalized Probabilistic Descent Method Tsuneo NITTA, Akinori KAWAMURA, Yasuyuki MASAI, Akira NAKAYAMA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The hybrid algorithm of SMQ (Statistical Matrix Quantization) and HMM shows high performance in vocabulary-unspecific, speaker-independent speech recognition, however, it needs lots of computation and memory at a segment quantizer of SMQ. In this paper, we propose a newly developed, two-stage segment quantizer with a feature extractor based on KL-expansion and a classifier, both are traind by using competitive training of MCE/GPD. Result of experiments shows 1/30 1/40 reduction in both computation time and a memory size with the same perfomance that the old version of SMQ shows. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Speech Recognition / HMM / Segment Quantization / Competitive Training / KL-expansion / GPD |
Paper # | SP96-94 |
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Committee | SP |
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Conference Date | 1997/1/16(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Speech (SP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | High-speed Segment Quantization Based on KL-expansion and Generalized Probabilistic Descent Method |
Sub Title (in English) | |
Keyword(1) | Speech Recognition |
Keyword(2) | HMM |
Keyword(3) | Segment Quantization |
Keyword(4) | Competitive Training |
Keyword(5) | KL-expansion |
Keyword(6) | GPD |
1st Author's Name | Tsuneo NITTA |
1st Author's Affiliation | Toshiba Multimedia Eng. Lab.() |
2nd Author's Name | Akinori KAWAMURA |
2nd Author's Affiliation | Toshiba Multimedia Eng. Lab. |
3rd Author's Name | Yasuyuki MASAI |
3rd Author's Affiliation | Toshiba Multimedia Eng. Lab. |
4th Author's Name | Akira NAKAYAMA |
4th Author's Affiliation | Toshiba Multimedia Eng. Lab. |
Date | 1997/1/16 |
Paper # | SP96-94 |
Volume (vol) | vol.96 |
Number (no) | 448 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |