2014
DOI: 10.3989/loquens.2014.009
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Toward a unified theory of voice production and perception

Abstract: At present, two important questions about voice remain unanswered: When voice quality changes, what physiological alteration caused this change, and if a change to the voice production system occurs, what change in perceived quality can be expected? We argue that these questions can only be answered by an integrated model of voice linking production and perception, and we describe steps towards the development of such a model. Preliminary evidence in support of this approach is also presented. We conclude that… Show more

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Cited by 77 publications
(60 citation statements)
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“…1 The source spectrum was then smoothed by fitting it with a four-piece model whose segments ranged from the first to the second harmonic (H1-H2), from H2 to the harmonic nearest 2 kHz (H2-2 kHz), from the harmonic nearest 2 kHz to that nearest 5 kHz (2-5 kHz), and from H2 to the harmonic nearest 5 kHz (H2-5 kHz). These segments were chosen because they capture most of the variability in source spectral shapes (Kreiman, Gerratt, & Antoñanzas-Barroso, 2007a), their individual perceptual importance has been established (Garellek, Keating, Esposito, & Kreiman, 2013;Kreiman & Garellek, 2011), and in combination, they appear to form an adequate psychoacoustic model of source contributions to voice quality (Garellek, Samlan, Gerratt, & Kreiman, 2016;Kreiman, Garellek, Chen, Alwan, & Gerratt, 2015;Kreiman, Gerratt, Garellek, Samlan, & Zhang, 2014). These measures were thus preferred to others found in the literature (jitter, shimmer, etc.)…”
Section: Acoustic Evaluationmentioning
confidence: 99%
“…1 The source spectrum was then smoothed by fitting it with a four-piece model whose segments ranged from the first to the second harmonic (H1-H2), from H2 to the harmonic nearest 2 kHz (H2-2 kHz), from the harmonic nearest 2 kHz to that nearest 5 kHz (2-5 kHz), and from H2 to the harmonic nearest 5 kHz (H2-5 kHz). These segments were chosen because they capture most of the variability in source spectral shapes (Kreiman, Gerratt, & Antoñanzas-Barroso, 2007a), their individual perceptual importance has been established (Garellek, Keating, Esposito, & Kreiman, 2013;Kreiman & Garellek, 2011), and in combination, they appear to form an adequate psychoacoustic model of source contributions to voice quality (Garellek, Samlan, Gerratt, & Kreiman, 2016;Kreiman, Garellek, Chen, Alwan, & Gerratt, 2015;Kreiman, Gerratt, Garellek, Samlan, & Zhang, 2014). These measures were thus preferred to others found in the literature (jitter, shimmer, etc.)…”
Section: Acoustic Evaluationmentioning
confidence: 99%
“…In a recent paper, Kreiman et al (2014) proposed a psychoacoustic model designed to capture the relationship between the acoustic voice signal and overall perceived voice quality. 1 Such a model is an essential component of a theory linking voice production to perception, so that when changes in the vocal production system cause changes to the acoustic signal, the acoustic changes can be used to predict the change in voice quality.…”
Section: Introductionmentioning
confidence: 99%
“…The present results suggest an alternative approach: determining the spectral features of sounds that predict what listeners hear, and then seeking (and modeling) the timedomain causes of those specific spectral changes. This alternative has received little attention (but see Kreiman et al, 2014). Traditionally, spectral-domain modeling of the voice source was discouraged because it was time-consuming, yielded artifacts, and still required some temporal information, such as period length.…”
Section: General Discussion and Conclusionmentioning
confidence: 99%
“…However, these concerns have become largely irrelevant. Computational constraints and artifacts are no longer common Kreiman et al, 2010), and much progress has been made in determining spectral parameters that vary across voices and to which listeners are sensitive (Kreiman et al, 2007a;Kreiman et al, 2014). Both approaches (modeling in the time domain vs in the spectral domain) share the goal of mapping between voice production and perception; but in the second case the functional significance of the magic moments or places is established a priori, ensuring that results will be perceptually meaningful, however complex the associations between physical and psychoacoustic events prove to be.…”
Section: General Discussion and Conclusionmentioning
confidence: 99%
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