Voice Source Variation and Its Communicative Functions

Gobl, Christer; Chasaide, Ailbhe Nı́

doi:10.1002/9781444317251.ch11

Cited by 50 publications

(64 citation statements)

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“…However, as discussed in Sec. I, the correspondence between timing events and spectral configuration is hardly straightforward (Fant and Lin, 1988;Henrich et al, 2001;Gobl and N ı Chasaide, 2010). 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.…”

Section: General Discussion and Conclusionmentioning

confidence: 99%

“…The Rosenberg model (Rosenberg, 1971), in contrast to the other models, describes the opening and closing phases of the glottal flow volume velocity with separate trigonometric functions that incorporate two timing parameters and one amplitude parameter. In comparison, the six-parameter Fujisaki-Ljungqvist model and the four-parameter LF model represent the first derivative of the glottal volume velocity pulse, which incorporates lip radiation effects (Gobl and N ı Chasaide, 2010). The LF model (Fant et al, 1985) combines an exponentially increasing sinusoidal function and an exponential function with one amplitude parameter (E e ) and three time points; the Fujisaki-Ljungqvist model (Fujisaki and Ljungqvist, 1986) uses polynomials to model the shape and duration of different segments of the flow derivative waveform.…”

Section: A the Source Modelsmentioning

confidence: 99%

“…One possibility for bridging the gap between the time and spectral domains is to convert temporal parameters into spectral ones (Ananthapadmanabha, 1984;Fant and Lin, 1988;Doval et al, 2006;Kane et al, 2010). However, the correspondence between time-and spectral-domain parameters is usually not straightforward (Fant and Lin, 1988;Gobl and N ı Chasaide, 2010), and pulse shape changes have effects throughout the spectrum, rather than altering one specific spectral component Henrich et al, 2001). For example, Henrich et al (2001) found that H1*-H2*, 1 which is a perceptually meaningful component of the voice spectrum (Esposito, 2010), could be modeled only by using a combination of time-domain parameters, rather than by a single parameter (cf.…”

mentioning

confidence: 99%

“…As presently implemented, most models of the voice source describe time-domain features of vocal fold vibration or of glottal flow, including peak glottal opening/peak flow and the negative peak of the flow derivative, which is associated with the instant of maximum excitation (Fant, 1993). Models are typically evaluated in terms of their fit to empirical pulse shapes (e.g., Fujisaki and Ljungqvist, 1986;Gobl and N ı Chasaide, 2010;Shue and Alwan, 2010). For example, the LF model captures changes in the glottal flow derivative using sinusoidal and exponential functions (Fant et al, 1985), and Fant attributed its widespread use to its ability to capture "essentials" of a variety of glottal wave shapes (Fant, 1995, p. 119).…”

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confidence: 99%

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Perceptual evaluation of voice source models

Kreiman

Garellek

Chen

et al. 2015

The Journal of the Acoustical Society of America

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Models of the voice source differ in their fits to natural voices, but it is unclear which differences in fit are perceptually salient. This study examined the relationship between the fit of five voice source models to 40 natural voices, and the degree of perceptual match among stimuli synthesized with each of the modeled sources. Listeners completed a visual sort-and-rate task to compare versions of each voice created with the different source models, and the results were analyzed using multidimensional scaling. Neither fits to pulse shapes nor fits to landmark points on the pulses predicted observed differences in quality. Further, the source models fit the opening phase of the glottal pulses better than they fit the closing phase, but at the same time similarity in quality was better predicted by the timing and amplitude of the negative peak of the flow derivative (part of the closing phase) than by the timing and/or amplitude of peak glottal opening. Results indicate that simply knowing how (or how well) a particular source model fits or does not fit a target source pulse in the time domain provides little insight into what aspects of the voice source are important to listeners.

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Section: General Discussion and Conclusionmentioning

confidence: 99%

Section: A the Source Modelsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Perceptual evaluation of voice source models

Kreiman

Garellek

Chen

et al. 2015

The Journal of the Acoustical Society of America

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“…Tulemus oleneb aga üsna palju protseduuri teostaja subjektiivsetest valikutest formantsageduste määramisel. Samuti pole välistatud artefaktide esinemine ning isegi teoreetiliselt puudub võimalus hinnata meetodi täpsust (Gobl & Ni Chasaide 2012). Ka larüngograafi signaali põhjal tehtavate järelduste puhul pole võimalik elimineerida nende teatud ebakindlust, sest graafiku kuju, mis on iseloomulik häälepilu sulgumisele, võib esineda ka siis, kui täielikku sulgumist ei toimugi (Colton & Conture 1990).…”

Section: Allan Vurmaunclassified

Hääle spektri mähiskõvera kuju stabiilsus varieeruva dünaamikaga heliredelite laulmisel

Vurma

2017

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Teesid: Käesoleva töö eesmärk oli uurida, kas ja kuidas muutuvad klassikaliselt treenitud lauljate hääle tämbriga seotud akustilised parameetrid, kui laulda hääle dünaamikat ja helikõrgust muutes. Uurimust motiveeris läbi viima vokaalpedagoogilises kirjanduses sageli väljendatud seisukoht, et klassikalise laulutreeningu üks eesmärk on hääle kõlalise ühtluse saavutamine. Palusime kümnel meeslauljal (kelle hulgas olid ooperi-ja oratooriumisolistid ning laulueriala üliõpilased) laulda ühe oktavi ulatusega tõusvaid D-duuri gammasid (vahemikus d -d 1 ) kolmel moel: (1) kõige harjumuspärasema dünaamikaga, (2) häälevaljust kasvatades ja (3) häälevaljust kahandades. Salvestasime esitused väikese reverberatsiooniga helistuudios. Tarkvara Sopran 1.0.10 abil arvutasime iga lauldud noodi keskmise võimsusspektri, kus määrasime põhitooni ja lauljaformandi spektripiirkondade tugevused spektri kõige tugevama tipu taseme suhtes. Mõõtsime iga lauldud noodi puhul ka helirõhu taseme ja glotaalse aduktsiooni tugevust iseloomustavate sulguskvotsiendi ja kvaasikontaktkvotsiendi väärtused. Uuringutulemused näitasid, et vastavad parameetrid muutusid ülesannete täitmisel süstemaatiliselt kõigi lauljate puhul. Osa kirjeldatud muutustest tingisid puht-akustilised faktorid, mida vokalist ei saa vokaaltehnikaga mõjutada. Mõni laulja kasutas vokaaltehnilisi võtteid, mille eesmärgiks võis olla häälekõla tajutava ühtluse parandamine. Üks taolisi võtteid oli piano ja forte vahelise erinevuse tekitamine eelkõige hääle tämbri, mitte aga niivõrd otsese helirõhu taseme abil. Vastupidiseks strateegiaks oli just helirõhu taseme muutmine, samal ajal hääletämbri kanduvuse ja ereduse aspektiga seotud lauljaformandi suhtelise tugevuse varieerumist väiksena hoides. Hääle tajutav ühtlus võib olla seotud veel hääle mõningate omadustega, mida käesolevas töös lähemalt ei käsitletud. Hääleparameetrite väärtuste varieerumise viis sõltuvalt helikõrgusest ja dünaamikast võib oleneda ka häälikust, mida laulmisel kasutatakse ning helikõrguse piirkonnast.

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Vocal indicators of facilitative interpersonal skills

Glasgow

Anderson

Lee

et al. 2022

Couns and Psychother Res

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It has long been recognised that therapist reactions during difficult relational impasses with clients are implicated in psychotherapy outcomes and processes (Eubanks-Carter et al., 2015;Safran & Muran, 2000;Strupp & Binder, 1984). For example, Strupp (1997) noted that even highly experienced professional therapists had remarkable variation in how they responded to the most challenging situations with clients. Additionally, how therapists respond can significantly influence their clients (Henry et al., 1990). Building on this research and common factors theory, the facilitative interpersonal skills research method (FIS;Anderson et al., 2009Anderson et al., , 2016 exposes therapists to several challenging therapy situations, all through video simulations of standardised clients. Therapists and helpers respond to these standardised, realistic and challenging client verbalisations, and their responses are evaluated independently by trained coders.Evidence has shown that therapist facilitative responses to these challenging situations are predictive of client outcomes (Anderson et al., 2009(Anderson et al., , 2016, such that therapists who exhibit interpersonal skills tend to have relatively better outcomes with their clients.However, the behaviours of therapists during the FIS task are not well understood. What are therapists and helpers expressing, how are they expressing it, and what is contributing to FIS scores (which, in turn, are implicated in client outcomes)? The most immediate response to these questions involves the relational qualities being rated on the FIS; however, it is important to understand more about what is involved in these relational qualities.

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Voice Source Variation and Its Communicative Functions

Cited by 50 publications

References 0 publications

Perceptual evaluation of voice source models

Perceptual evaluation of voice source models

Hääle spektri mähiskõvera kuju stabiilsus varieeruva dünaamikaga heliredelite laulmisel

Vocal indicators of facilitative interpersonal skills

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