Voice Source State as a Source of Information in Speech Recognition: Detection of Laryngealizations

Laryngealizations are irregular voiced portions of speech, which can have morphosyntactic functions and can disturb the automatic computation of F0. Two methods for the automatic detection of laryngealizations are described in this paper: With a Gaussian classifier using spectral and cepstral features a recognition rate of 80% (false alarm rate of 8%) could be achieved. As an alternative a “non-standard” method has been developed: an artificial neural network (ANN) was used for non-linear inverse filtering of speech signals. The inversely filtered signal was directly used as input for another ANN, which was trained to detect laryngealizations. In preliminary experiments we obtained a recognition rate of 65% (12% false alarms).