Finite register length effects in a hidden Markov model speech recognizer
| Autor: | Wu-Ji Yang, Hsiao-Chuan Wang |
|---|---|
| Rok vydání: | 1990 |
| Předmět: |
Linguistics and Language
Relation (database) business.industry Computer science Communication Speech recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Realization (linguistics) Computer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing) Pattern recognition Markov model Language and Linguistics Computer Science Applications Parallel processing (DSP implementation) Register (music) Computer Science::Sound Modeling and Simulation Range (statistics) Computer Vision and Pattern Recognition Artificial intelligence Hidden Markov model business Software Statistic |
| Zdroj: | Speech Communication. 9:239-245 |
| ISSN: | 0167-6393 |
| DOI: | 10.1016/0167-6393(90)90060-m |
| Popis: | This paper presents a study on finite-register-length effects in a Hidden Markov Model speech recognizer. A statistic model is utilized to approximate the distribution of the score differences. The range of recognition rate due to quantization noise on HMM parameters is calculated by using the statistic model. Then the relation between the recognition rate and the quantization noise is derived. This provides the information for determining the register length in the hardware realization of a HMM speech recognizer. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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