Speech variablity in speaker recognization system

Several algorithms have been developed for extracting the formant information from speech signals however most of these algorithms are either not robust in real-life noise environments or are not suitable for real-time implementation. Two algorithms are discussed in the present work. One is Robust formant tracking algorithm and other is Recursive least square algorithm (RLS). The first algorithm achieves formant extraction from continuous speech by using a time-varying adaptive filter bank to track and estimate individual formant frequencies. The formant tracker incorporates an adaptive voicing detector and a gender detector for robust formant extraction from continuous speech. And the second algorithm is based on recursive least square values. Forgetting factor approach is used for estimating formant frequencies with RLS algorithm.