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Recently developed speech technology platforms, such as statistical speech synthesis and voice transformation systems, facilitate the modification of voice characteristics. To fully exploit the potential of such platforms, speech analysis algorithms need to be able to handle the different acoustic characteristics of a variety of voice qualities. Glottal closure instant (GCI) detection is typically required in the analysis stages, and thus the importance of robust GCI algorithms is evident. The current study examines some important analysis signals relevant to GCI detection, for a range of phonation types. Furthermore, a new algorithm is proposed which builds on an existing GCI algorithm to optimise the performance when analysing speech involving different phonation types. Results suggest improvements in the GCI detection rate for creaky voice due to a reduction in false positives. When there is a lack of prominent peaks in the Linear Prediction residual, as found for breathy and harsh voice, the results further indicate some enhancement of GCI identification accuracy for the proposed method.

This paper explores the role of voice quality in the communication of emotions, moods and attitudes. Listeners' reactions to an utterance synthesised with seven different voice qualities were elicited in terms of pairs of opposing affective attributes. The voice qualities included harsh voice, tense voice, modal voice, breathy voice, whispery voice, creaky voice and lax-creaky voice. These were synthesised using a formant synthesiser, and the voice source parameter settings were guided by prior analytic studies as well as auditory judgements. Results offer support for some past observations on the association of voice quality and affect, and suggest a number of refinements in some cases. Listeners' ratings further suggest that these qualities are considerably more effective in signalling milder affective states than the strong emotions. It is clear that there is no one-to-one mapping between voice quality and affect: rather a given quality tends to be associated with a cluster of affective attributes.

Instabilities of the human voice source appear in normal voices under certain conditions (newborn cries, vocal fry, creaky voice) and are symptomatic of voice pathologies. Vocal instabilities are intimately related to bifurcations of the underlying nonlinear dynamical system. We analyse in this paper bifurcations in 2-mass models of the vocal folds and study, in particular, how the incorporation of the vocal tract affects bifurcation diagrams. A comparison of a simplified model (Steinecke and Herzel, 1995) with an extended version including vocal tract resonances reveals that essential features of the bifurcation diagrams (as e.g. frequency locking of both folds and toroidal oscillations) are found in both model versions. However, vocal instabilities appear in the extended model at lower subglottal pressures and even for weak asymmetries.

Subtle variations in voice (phonatory) quality may reveal aspects of the speaker's mood and attitude, and are thus an important aspect of speaking style. This paper illustrates current research being carried out by the authors on the voice source correlates of a range of such quality differences. The voice qualities looked at include modal, breathy, whispery, tense, lax and creaky voice, following the description of Laver (1980) and analyses presented here focus on a word extracted from a propose passage read with these qualities. The principal method used for analysing the voice source involved inverse filtering of the speech wave. In order to quantify the source characteristics, a four parameter voice source model (the LF-model) was matched to the inverse filtered waveform. Frequency domain analyses of the speech waveform, based on narrow band spectral sections and on spectral averaging, were also carried out. Detailed comparisons of the data measured directly from the glottal waveform and those measured from the speech output yield insights which could not be inferred from either alone. Results suggest a number of important differences between the qualities as well as considerable dynamic variation within a single quality. The data should also prove useful for resynthesis, which is an important tool for testing perceptual aspects of voice quality; e.g., the attitudinal and emotional colouring that may be associated with particular voice qualities.