The development of sex/gender-specific /s/ and its relationship to gender identity in children and adolescents

Li, Fangfang; Rendall, Drew; Vasey, Paul L.; Kinsman, Melissa; Ward-Sutherland, Amanda; Diano, Giancarlo

doi:10.1016/j.wocn.2016.05.004

Cited by 21 publications

(6 citation statements)

References 61 publications

(67 reference statements)

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“…Drager, 2011; Kohn and Farrington, 2012; Alam and Stuart-Smith, 2014; Li et al, 2016, among many others). This leads to potentially large pools of more or less fluent socially-motivated variation, as boys and girls negotiate gender-specific, group-specific, cohort-specific, or even clique-specific pronunciation habits that will continue to evolve even as they grow into adolescents who must further adjust their speech motor habits to the physiological changes to the vocal tract and glottis that are associated with hormonal changes at puberty.…”

Section: How and Why Standard Asr Methods Fail For Child Speechmentioning

confidence: 97%

Methods for eliciting, annotating, and analyzing databases for child speech development

Beckman

Plummer

Munson

et al. 2017

Computer Speech & Language

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Methods from automatic speech recognition (ASR), such as segmentation and forced alignment, have facilitated the rapid annotation and analysis of very large adult speech databases and databases of caregiver-infant interaction, enabling advances in speech science that were unimaginable just a few decades ago. This paper centers on two main problems that must be addressed in order to have analogous resources for developing and exploiting databases of young children's speech. The first problem is to understand and appreciate the differences between adult and child speech that cause ASR models developed for adult speech to fail when applied to child speech. These differences include the fact that children's vocal tracts are smaller than those of adult males and also changing rapidly in size and shape over the course of development, leading to between-talker variability across age groups that dwarfs the between-talker differences between adult men and women. Moreover, children do not achieve fully adult-like speech motor control until they are young adults, and their vocabularies and phonological proficiency are developing as well, leading to considerably more within-talker variability as well as more between-talker variability. The second problem then is to determine what annotation schemas and analysis techniques can most usefully capture relevant aspects of this variability. Indeed, standard acoustic characterizations applied to child speech reveal that adult-centered annotation schemas fail to capture phenomena such as the emergence of covert contrasts in children's developing phonological systems, while also revealing children's nonuniform progression toward community speech norms as they acquire the phonological systems of their native languages. Both problems point to the need for more basic research into the growth and development of the articulatory system (as well as of the lexicon and phonological system) that is oriented explicitly toward the construction of age-appropriate computational models.

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Section: How and Why Standard Asr Methods Fail For Child Speechmentioning

confidence: 97%

Methods for eliciting, annotating, and analyzing databases for child speech development

Beckman

Plummer

Munson

et al. 2017

Computer Speech & Language

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show abstract

“…The rejection of frequencies over 4000 Hz affects especially high frequency sounds such as sibilants (Niemi-Laitinen 1999); For example, previous studies have reported that the way of production of /s/ is related to the speaker's gender (Li et al 2016), and even to male speakers' sexual orientation (Tracy et al 2015). Therefore, necessary information for speaker profiling might be lacking from the call recordings due to limited transmitted frequencies.…”

Section: Acoustic Measurement Techniquementioning

confidence: 99%

Classifying females’ stressed and neutral voices using acoustic–phonetic analysis of vowels: an exploratory investigation with emergency calls

Tavi

2018

Int J Speech Technol

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In the present exploratory study, we investigated acoustic-phonetic measures of spoken vowels for detection of female speech under conditions of stress. Eight authentic recorded calls to emergency services received from eight Finnish adult female speakers were chosen for the analysis. Based on the purpose of the call, the recordings were divided into two groups: the stressed group and the neutral group. We chose f0, H1-H2 and centre of gravity as acoustic-phonetic predictors for our final classification models; In previous studies, high f0 has been associated with a stressed voice, but H1-H2 and centre of gravity have not previously been related to speech under stress. On the other hand, H1-H2 has been used to detect non-modal voice qualities, such as a creaky or breathy voice, and similar voice qualities have been observed in stressed speech. Furthermore, indications exist that in speech under stress, acoustic energy is concentrated in higher frequencies, which consequently increases the centre of gravity. We tested stress detection accuracy with three statistical classifiers: LDA, logistic regression and decision tree. Our results indicated that all the models performed better when they were trained using only the vowel /i/ rather than training them with all Finnish vowels. The use of our best performing model, a logistic regression model based on /i/, yielded 88% correct classification, whereas a logistic regression model trained with all vowels achieved an accuracy of only 81%. We conclude that the results indicate a good stress classification accuracy, although further research with more extensive data is required.

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“…Earlier research determined how linguistic categories, such as the place of articulation and voicing shape the spectral properties of fricatives (e.g., Hughes and Halle, 1956 ; Nittrouer et al, 1989 ; Baum and McNutt, 1990 ; Ladefoged and Maddieson, 1996 ; Jongman et al, 2000 ; Fox and Nissen, 2005 ; Shadle, 2010 ; Iskarous et al, 2011 ; Koenig et al, 2013 ), yet most of these findings are based on acoustic evidence from a single language variety (e.g., for Korean fricatives see Cho et al, 2002 , for English fricatives see Tabain, 1998 ; Jongman et al, 2000 ; Iskarous et al, 2011 ). Despite the fact that a number of earlier studies showed that social factors, such as gender and age (e.g., see Jongman et al, 2000 ; Fox and Nissen, 2005 ; Li et al, 2016 ), education, social identity, social networks (e.g., Baran, 2014 ) and the place of origin, urban vs. rural (Dubois and Horvath, 1998 ; Kochetov, 2006 ; Stuart-Smith, 2007 ; Mazzaro, 2011 ) have significant effects on fricatives, the effects of dialect on fricatives acoustic structure are understudied.…”

Section: Introductionmentioning

confidence: 96%

Effects of Two Linguistically Proximal Varieties on the Spectral and Coarticulatory Properties of Fricatives: Evidence from Athenian Greek and Cypriot Greek

Themistocleous¹

2017

Front. Psychol.

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Several studies have explored the acoustic structure of fricatives, yet there has been very little acoustic research on the effects of dialects on the production of fricatives. This article investigates the effects of two linguistically proximal Modern Greek dialects, Athenian Greek and Cypriot Greek on the temporal, spectral, and coarticulatory properties of fricatives and aims to determine the acoustic properties that convey information about these two dialects. Productions of voiced and voiceless labiodental, dental, alveolar, palatal, and velar fricatives were extracted from a speaking task from typically speaking female adult speakers (25 Cypriot Greek and 20 Athenian Greek speakers). Measures were made of spectral properties, using a spectral moments analysis. The formants of the following vowel were measured and second degree polynomials of the formant contours were calculated. The findings showed that Athenian Greek and Cypriot Greek fricatives differ in all spectral properties across all places of articulation. Also, the co-articulatory effects of fricatives on following vowel were different depending on the dialect. Duration, spectral moments, and the starting frequencies of F1, F2, F3, and F4 contributed the most to the classification of dialect. These findings provide a solid evidence base for the manifestation of dialectal information in the acoustic structure of fricatives.

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The development of sex/gender-specific /s/ and its relationship to gender identity in children and adolescents

Cited by 21 publications

References 61 publications

Methods for eliciting, annotating, and analyzing databases for child speech development

Methods for eliciting, annotating, and analyzing databases for child speech development

Classifying females’ stressed and neutral voices using acoustic–phonetic analysis of vowels: an exploratory investigation with emergency calls

Effects of Two Linguistically Proximal Varieties on the Spectral and Coarticulatory Properties of Fricatives: Evidence from Athenian Greek and Cypriot Greek

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