Noisy Speech Recognition Using Kernel Fuzzy C Means
| Autor: | H. Y. Vani, M. A. Anusuya |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Soft computing
Computer science Speech recognition 02 engineering and technology Function (mathematics) Signal Fuzzy logic 030507 speech-language pathology & audiology 03 medical and health sciences Computer Science::Sound Computer Science::Computer Vision and Pattern Recognition Kernel (statistics) Word recognition 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0305 other medical science |
| Zdroj: | Communications in Computer and Information Science ISBN: 9789811090585 |
| Popis: | In the area of voice recognition, soft computing technique is a prominent method to identify and cluster speaker variability’s in the speech signal. But whenever the signal is convoluted by a noisy signal standard FCM method fails to give the good results. To overcome this, Kernel FCM (KFCM) is used in this paper. PCA helps in reducing the features of convoluted signal. The recognition results are compared with and without applying PCA using KFCM function and the same is presented for word recognition rate. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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