Fourth European Conference on Speech Communication and Technology

Madrid, Spain
September 18-21, 1995

Characterization of Spectral Transition Region by Various Prediction Approaches for Discriminating Stop Consonants

P. V. S. Rao, R. Raveendran

Computer Systems and Communications Group, Tata Institute of Fundamental Research, Bombay, India

A comparative study of a scalar waveform modelling approaches based on linear, quadratic and neural prediction techniques was performed. A linear spectral predictor model was also studied on two spectral representations. For this, we consider the task of discriminating the places of articulation of stop consonants using their spectral transition information. A modified error measure has been defined and shown to be effective in reducing the pitch interference effect that arise in directly modelling the waveform. The importance of complete spectral information of the vocal tract system dynamics and the significance of higher order correlation in the recognition performance have been highlighted.

Full Paper

Bibliographic reference.  Rao, P. V. S. / Raveendran, R. (1995): "Characterization of spectral transition region by various prediction approaches for discriminating stop consonants", In EUROSPEECH-1995, 1393-1396.