On the robust incorporation of formant features into hidden Markov models for automatic speech recognition

A formant analyser is interpreted probabilistically via a noisy channel model. This leads to a robust method of incorporating formant features into hiddenMarkov models for automatic speech recognition. Recognition equations follow trivially, and Baum-Welch style re-estimation equations are derived. Experimental results are presented which provide empirical proof of convergence, and demonstrate the e ectiveness of the technique in achieving recognition performance advantages by including formant features rather than only using cepstrum features.