Using formant frequencies in speech recognition

Abstract

Formant frequencies have rarely been used as acoustic features for speech recognition, in spite of their phonetic significance. For some speech sounds one or more of the formants may be so badly defined that it is not useful to attempt a frequency measurement. Also, it is often difficult to decide which formant labels to attach to particular spectral peaks. This paper describes a new method of formant analysis which includes techniques to overcome both of the above difficulties. Using the same data and HMM model structure, results are compared between a recognizer using conventional cepstrum features and one using three formant frequencies, combined with fewer cepstrum features to represent general spectral trends. For the same total number of features, results show that including formant features can offer increased accuracy over using cepstrum features only.