Application of Markov random fields to formant extraction

The theory of Markov random fields (MRFs) is used to extract formants from linear predictive coding (LPC) pole locations. In this model, the spectral peaks are presented in a time-frequency plot, using LPC poles as noisy indications of these peaks, and the formants are represented as lines connecting the spectral peaks. The spectral peaks and formants are modeled by a site process MRF and a line process MRF, respectively. The a posteriori probability of the spectral peaks and formants, given the LPC poles, quantifies the continuity constraints on the formants, the relationship between spectral peaks and formant locations, and the noise of the LPC poles. The formants are chosen by maximizing the a posteriori probability using simulated annealing. The parameters characterizing the MRFs are estimated by maximizing a pseudolikelihood function derived from LPC pole data with correctly labeled formants