| Presentation | 2004/12/13 Robust Acoustic Modeling for Speech Recognition Koichi SHINODA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | While Hidden Markov Models (HMMs) have been successfully applied to automatic speech recognition, they are not still robust enough against differences in speakers, speaking-styles, and environmental noises. To tackle this problem, we need to study the inner structure of speech by using large corpus and rich computational power. In this direction, the model size tends to be increase and hence the data insufficiency problem becomes more serious. In this paper, we focus on robust modeling against data insufficiency. Approaches based on information criteria such as Minimum Description Length and structural approaches in which models are changed according to the amount of data availabl are discussed.. While these techniques have been important for HMM research, it will be more important in the research beyond HMM. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | acoustic modeling / information criterion / distance measure / MDL / SMAP |
| Paper # | NLC2004-42,SP2004-82 |
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| Conference Information | |
| Committee | NLC |
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| Conference Date | 2004/12/13(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | |
| Vice Chair | |
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| Paper Information | |
| Registration To | Natural Language Understanding and Models of Communication (NLC) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Robust Acoustic Modeling for Speech Recognition |
| Sub Title (in English) | |
| Keyword(1) | acoustic modeling |
| Keyword(2) | information criterion |
| Keyword(3) | distance measure |
| Keyword(4) | MDL |
| Keyword(5) | SMAP |
| 1st Author's Name | Koichi SHINODA |
| 1st Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology() |
| Date | 2004/12/13 |
| Paper # | NLC2004-42,SP2004-82 |
| Volume (vol) | vol.104 |
| Number (no) | 538 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |