A robust speech analysis in speech recognition
| Autor: | Yoshikazu Miyanaga, N. Ohtsuki, S. Gozen |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
Voice activity detection
Computer science business.industry Speech recognition Noise reduction Speech coding Acoustic model Computer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing) Pattern recognition Linear predictive coding Speaker recognition Speech processing Adaptive filter Computer Science::Sound Distortion Artificial intelligence Hidden Markov model business |
| Zdroj: | WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000. |
| DOI: | 10.1109/icosp.2000.891608 |
| Popis: | This report presents an adaptive speech analysis method specially used for a speech recognition system. The designed speech recognition system consists of an adaptive speech analysis, a self-organized clustering/pseudo-labeling method and a DTW. All methods are redesigned in fully parallel and pipelined mechanism. In the speech analysis method, an adaptive ARMA lattice modelling is introduced for the reduction of distortion, noise and disturbance. In addition, the speech analysis keeps robust condition where an adaptive method is usually considered to be sensitive as to the convergence property and the parameter estimation. By using the recognition system including the robust adaptive speech analyzer, speech recognition results are shown. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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