On the Use of a Spectral Glottal Model for the Source-filter Separation of Speech

Olivier Perrotin (1) , Ian V. Mcloughlin (1)

1 University of Kent [Canterbury]

The estimation of glottal flow from a speech waveform is a key method for speech analysis and parameterization. Significant research effort has been made to dissociate the first vocal tract resonance from the glottal formant (the low-frequency resonance describing the open-phase of the vocal fold vibration). However few methods cope with estimation of high-frequency spectral tilt to describe the return-phase of the vocal fold vibration, which is crucial to the perception of vocal effort. This paper proposes an improved version of the well-known Iterative Adaptive Inverse Filtering (IAIF) called GFM-IAIF. GFM-IAIF includes a full spectral model of the glottis that incorporates both glottal formant and spectral tilt features. Comparisons with the standard IAIF method show that while GFM-IAIF maintains good performance on vocal tract removal, it significantly improves the perceptive timbral variations associated to vocal effort.

Domaines: Traitement du signal et de l'image [eess.SP]; Interface homme-machine [cs.HC]

Olivier Perrotin, Ian V. Mcloughlin. On the Use of a Spectral Glottal Model for the Source-filter Separation of Speech. 2019. ⟨hal-01971707v1⟩