Automatic classification of pitch movements via MLP-based estimation of class probabilities

In this paper, we study to what extent pitch movements in utterances can be classified automatically by using acoustical information and an intonation grammar. It will be shown that pitch movements can be classified into six categories with an agreement of about 80 percent compared with human transcriptions, on the basis of the pitch contour and the moments of vowel onsets. These six categories cover about 90 percent of all pitch movements used in the database (elicited speech). Results involving an intonation grammar are also presented