| Autor: |
Priyadarshani, P. G. N., Dias, N. G. J., Punchihewa, Amal |
| Zdroj: |
2012 IEEE 55th International Midwest Symposium on Circuits & Systems (MWSCAS); 1/ 1/2012, p896-899, 4p |
| Abstrakt: |
For centuries, researchers around the world have attempted to develop a natural interface between human and computer that enables the computer to speak and understand the natural language as the humans do. Even speech recognition systems for some recognized languages have been developed to some extent; still people prefer to work with their native language. On the other hand, speaker dependability has been a major issue in many cases and majority of users prefer if the recognizer is independent of speaker because in a speaker dependent platform, each user has to undergo training phase as the recognizer does not keep reference templates for each potential user. In this research, Genetic Algorithm (GA) was successfully applied with Mel Frequency Cepstral Coefficients (MFCC) to identify separately pronounced Sinhala words in both speaker independent and speaker dependent platforms. [ABSTRACT FROM PUBLISHER] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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