Abstract
AbstractThe recognition of vowels in Chinese speech is very important for Chinese speech recognition and understanding. However, it is rather difficult and there has been no efficient method to solve it yet. In this paper, we propose a new approach to the recognition of Chinese vowels via the support vector machine (SVM) with the Mel-Frequency Cepstral Coefficients (MFCCs) as the vowel’s features. It is shown by the experiments that this method can reach a high recognition accuracy on the given vowels database and outperform the SVM with the Linear Prediction Coding Cepstral (LPCC) coefficients as the vowel’s features.KeywordsSupport Vector MachineRadial Basis FunctionSpeech SignalRecognition AccuracyLinear Support Vector MachineThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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