Abstract
In this paper some of the commonly used feature extraction techniques are presented and a new set of features based on the Discrete Wavelet Transform (DWT) and Admissible Wavelet Packet Transform (AWPT) is presented for the recognition of phonemes. These features overcome the problem of shift variance and speaker dependence encountered in the earlier features derived by using wavelet transform. Further study on the earlier proposed energy features derived by DWT is carried out and AWPT is proposed for phoneme recognition to overcome the problems with DWT based features. Further a new set of features based on the logarithmic compression of the energy is proposed which shows considerable improvement in the recognition performance.
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