Voice quality has been defined as the characteristic auditory colouring of an individual's voice, derived from a variety of laryngeal and supralaryngeal features and running continuously through the individual's speech. The distinctive tone of speech sounds produced by a particular person yields a particular voice. Voice quality is at the centre of several speech processing issues. In speech recognition, voice differences, particularly extreme divergences from the norm, are responsible for known performance degradations. In speech synthesis on the other hand, voice quality is a desirable modelling parameter, with millions of voice types that can be distinguished theoretically. This article reviews the experimental derivation of voice quality markers. Specifically, the use of perceptual judgements, the long-term averaged spectrum (LTAS) and prosodie markers is examined, as well as inverse filtering for the extraction of the glottal source waveform. This review suggests that voice quality is best investigated as a multi-dimensional parameter space involving a combination of factors involving individual prosody, temporally structured speech characteristics, spectral divergence and voice source features, and that it could profitably complement simple linguistic prosodic model processing in speech synthesis. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Keller, E. (2005). The analysis of voice quality in speech processing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3445 LNAI, pp. 54–73). Springer Verlag. https://doi.org/10.1007/11520153_4
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