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Un sistema híbrido basado en modelos ocultos de Markov y máquinas de vectores de soporte con aprendizaje hacia adelante para reconocimiento de fonos en habla continua venezolana
| Content Provider | Semantic Scholar |
|---|---|
| Author | Jabbour, Georges Maldonado, Luciano |
| Copyright Year | 2011 |
| Abstract | The performance of an automatic speech recognizer based on Hidden Markov Models (HMMs) and Support Vector Machines (SVMs) is here compared to the performance of two other recognizers: one based on HMMs only (the HMM recognizer), and the other is a hybrid model based on HMMs and SVMs (the HMM/SVM recognizer). The recognizer we propose here is called the SVM/HMM Hybrid Model with forward learning (the SVM/HMMFL recognizer). The three recognizers were programmed using Matlab and trained with Venezuelan continuous speech, the speech signals of which form part of the SpeechDat European project. The phone was chosen as the acoustic training unit. The recognition tests performed showed a significantly better performance of the hybrid recognizers when compared to that of the recognizers based on the HMMs only. Of the two hybrid recognizers, the best results were obtained with the SVM/HMMFL recognizer. |
| Starting Page | 7 |
| Ending Page | 16 |
| Page Count | 10 |
| File Format | PDF HTM / HTML |
| Volume Number | 18 |
| Alternate Webpage(s) | http://servicio.bc.uc.edu.ve/ingenieria/revista/v18n3/art01.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
