Estimating articulatory motion from speech wave

If articulatory movements can be estimated, then the articulatory parameters which represent the motion of the articulatory organs would be useful for speech recognition. This paper discusses an effective method of estimating articulatory movements and its application to speech recognition. Firstly, what is described is a method of estimating articulatory parameters known as the model matching method, and various spectral distance measures are evaluated for this method. The results show that the best in average is the higher order cepstral distance measure, which is one of the peak weighted measure. Secondly, articulatory parameters are utilized for the recognition of vowels uttered by unspecified speakers. It is shown that the adaptation of the model by the estimated mean vocal tract length is effective to normalize speaker difference. Thirdly, the motor commands to move the articulatory organs are estimated considering articulatory dynamics, and the continuous vowels are recognized by means of these estimated commands. It has been found that a considerable part of the coarticulation effects can be compensated for by this command estimated, and the method is useful for continuous speech recognition.