  Pitch and Formant frequencies are important features in speech processing
applications. The period of the vocal cord's output for vowels is known as the
pitch or the fundamental frequency, and formant frequencies are essentially
resonance frequencies of the vocal tract. These features vary among different
persons and even words, but they are within a certain frequency range. In
practice, just the first three formants are enough for the most of speech
processing. Feature extraction and classification are the main components of
each speech recognition system. In this article, two wavelet based approaches
are proposed to extract the mentioned features with help of the filter bank
idea. By comparing the results of the presented feature extraction methods on
several speech signals, it was found out that the wavelet transform has a good
accuracy compared to the cepstrum method and it has no sensitivity to noise. In
addition, several fuzzy based classification techniques for speech processing
are reviewed.
