Voice Quality: Functions, Analysis and Synthesis
August 27-29, 2003
We propose a more holistic approach to modelling of the glottal volume-velocita waveform and its derivative. Principal components analysis (PCA) is applied to single-cycle glottal waveforms measured in Laver's (1980) recorded speech data representing several phonation types. The first four principal component lend themselves to qualitative interpretations, and account for over 90% of the total variance. Decision trees generated using those components yield around 64% accuracy in classifying the 13 voice qualities analysed. This approach is capable of modelling a wide variety of voice qualities, and should therefore be useful in speech synthesis.
Bibliographic reference. Mokhtari, Parham / Pfitzinger, Hartmut R. / Ishi, Carlos Toshinori (2003): "Principal components of glottal waveforms: towards parameterisation and manipulation of laryngeal voice quality", In VOQUAL'03, 133-138.