Efficient speech recognition system for hearing impaired children in classical Tamil language
| Autor: | Revathi Arunachalam, Jeyalakshmi Chelliah |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Speech production
Point (typography) Computer science Speech recognition Biomedical Engineering 020207 software engineering 02 engineering and technology Pronunciation language.human_language 030507 speech-language pathology & audiology 03 medical and health sciences Tamil Stress (linguistics) 0202 electrical engineering electronic engineering information engineering language Mel-frequency cepstrum 0305 other medical science Cluster analysis Hidden Markov model |
| Zdroj: | International Journal of Biomedical Engineering and Technology. 26:84 |
| ISSN: | 1752-6426 1752-6418 |
| Popis: | This paper presents the development of the robust speech recognition system for the children with hearing impairment. It is a challenging task to recognise the distorted speeches of the hearing impaired since the characteristics of the speeches uttered by these people normally have variations in terms of accent, pronunciation and speed. Because of their inability to hear, they are not able to speak even though their nasal and oral cavities aiding for the speech production are perfect like normal persons. This work mainly emphasises the use of MFCC & MF-PLP features at the front end and HMM & K-means clustering at the back end. Performance of the system is evaluated and compared for the two modelling techniques and recognition accuracy is 94%, 97% and 84% for MFCC with HMM and accuracy is 98.3%, 93.5% and 93.6% for MF-PLP with K-means clustering for recognition system developed for recognising isolated digits, connected words and continuous speeches of hearing impaired. Noteworthy point to be mentioned is that, though the clustering technique is an old technique, it is proved that it gives better results as compared to HMM. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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