A new feature in speech recognition based on wavelet transform

Due to the excellent ability of dynamically adjusting the observation scope when the analyzing frequency changed, wavelet transform has been successfully applied to the processing of a non-stationary speech signal. We use the wavelet transform (WT) result and combine it with the traditional CEP vector (CEP-WT) to produce a new feature as the front-end output of an auto speech recognition system. Evaluation and experiments of the new feature show that the proposed method can improve the recognition system performance promisingly