Spoken arabic digits recognition based on wavelet neural networks

The paper describes a novel method for discrete speech recognition based on spoken Arabic digit recognition by means of wavelet neural network in which Morlet wavelet is introduced to the hidden layer. The speech signal is extracted by means of Mel Frequency Cepstral Coefficients (MFCCs) and followed by vector quantization (VQ). The experimental results obtained on a spoken Arabic digit dataset proved that it could achieve better accuracy and need less learning time than the proposed method.

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