Formant estimation algorithm based on pole focusing offering improved noise tolerance and feature resolution

The ability to measure the centre frequencies of areas of resonance (formants) in the short-time power spectrum of speech is of paramount importance in the recognition of voiced speech sounds in a feature-extraction-based continuous speech recognition system. Additionally, the provision of a tracking algorithm, by which the loci of formants with respect to time can be estimated, yields formant transition information which helps identify phonetic features which are of short duration. Noise robustness in formant estimation is an essential attribute for recognition systems which are used in the office environment and in military applications. The novel technique presented provides a noise-robust method of extracting formant centre-frequency information from the short-time speech spectrum, and consequently improves the signal/noise performance of the associated formant tracking algorithm.