Abstract:
An algorithm called maximum likelihood continuity mapping (MALCOM) will be presented. MALCOM recovers the positions of the tongue, jaw, and lips from measurements of the sound-pressure waveform of speech. Unlike other techniques for recovering articulator positions from speech, MALCOM does not require training on measured or modeled articulator positions, and MALCOM does not rely on any particular model of sound propagation through the vocal tract. The algorithm categorizes short-time windows of speech into a finite number of sound types, and assumes the probability of using any articulator position to produce a given sound type can be described by a parametrized probability density function. MALCOM uses maximum likelihood estimation techniques to: (1) find the most likely smooth articulator path given a speech sample and a set of probability density functions (one density function for each sound type); and (2) change the parameters of the probability density functions to better account for the data. The data set used for evaluating the continuity mapping algorithm is comprised of simultaneously collected articulator and acoustic measurements made using an electromagnetic midsagittal articulometer on a human subject. Comparisons between measured articulator positions and those recovered using continuity mapping will be presented. XXSU SC