The efficient discrete Tchebichef transform for spectrum analysis of speech recognition

Abstract

Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) is a famous technique to analyze frequency spectrum of the signal in speech recognition. The Discrete Tchebichef Transform (DTT) is proposed as possible alternative to the FFT. DTT has lower computational complexity and it does not require complex transform with imaginary numbers. This paper proposes an approach based on 256 discrete orthonormal Tchebichef polynomials for efficient to analyze a vowel and a consonant in spectral frequency of speech recognition. The comparison between 1024 discrete Tchebichef transform and 256 discrete Tchebichef transform has been done. The preliminary experimental results show that 256 DTT has the potential to be efficient to transform time domain into frequency domain for speech recognition. 256 DTT produces simpler output than 1024 DTT in frequency spectrum. The used of 256 Discrete Tchebichef Transform can produce concurrently four formants F 1 , F 2 , F 3 and F 4 for the consonant.