ESCA Workshop on Automatic Speaker Recognition, Identification, and Verification
The article concerns techniques for obtaining, representing and comparing voice source signals. Closed-phase formant frequencies and bandwidths were estimated by fitting two linear auto-regressive models to a glottal cycle (the first to the open, the second to the closed phase). The moment of switching from one sub-model to the next was automatically determined by minimizing the overall modelling error. The voice source signal was obtained by inverse filtering speech by means of the closed-phase formants. Its spectrum was represented by a nonlinear zero-memory Volterra model. Two source signals were compared by means of their minimal spectral distance which was obtained by adjusting the nonlinear gain of the Volterra model.
Bibliographic reference. Schoentgen, Jean / Azami, Zoubir (1994): "Closed-phase glottal inverse filtering by means of a compound auto-regressive model", In ASRIV-1994, 209-212.