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The development of lingual gestures in speech: an experimental approach to language development

2011· article· en· W1842632379 on OpenAlexaff
Lucie Ménard, Aude Noiray

Bibliographic record

VenueFaits de langues · 2011
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsCentre for Research on Brain Language and MusicUniversité du Québec à Montréal
FundersNational Institute on Deafness and Other Communication Disorders
KeywordsVocal tractGestureSpeech productionPsychologyCognitionCognitive psychologyPerceptionPerspective (graphical)Phonological ruleComputer sciencePhonologySpeech recognitionLinguisticsArtificial intelligence

Abstract

fetched live from OpenAlex

Learning to speak a language is related to the emergence of sensorimotor “maps” in which vowels and consonants are associated with articulatory-acoustic vocal tract configurations. One main challenge for young children is to develop these associations while integrating anatomical changes, as well as motor, perceptual, and cognitive abilities (Green, Moore, & Reilly, 2002; Kuhl & Meltzoff, 1982; Vorperian et al., 2005). There is empirical evidence that the physical growth in the vocal tract is not complete until adolescence (Kent, 2004). Hence, from birth to adulthood, the production of vowels and consonants is likely to reflect continuous articulatory and acoustic adjustments, as the production system matures. Determining the exact role of each component (anatomical, motor, perceptual, and cognitive) for producing intelligible speechis a complex task, especially from an ontogenetic perspective. The objective of this paper is to study the articulatory strategies used by children to produce speech targets. Those targets can be considered as phonological goals, implemented by phonetic articulatory gestures. Considering the facts that (i) 4-year-old children can produce intelligible phonemes, (ii) their motor control capacities are still immature, and (iii) their vocal tract anatomy greatly differs from that of adults, it is hypothesized that they use different phonetic strategies compared to adults to implement phonological targets. This report is part of a larger research program we have developed with our collaborators for the last decade (Menard et al., 2000; 2004). For the first time, this paper reports on articulatory data recorded via an ultrasound system. Data acquired by this method are compared to simulations with an articulatory-to-acoustic model (VLAM model), described below (Boe, 1999). 1.1. Non-Uniform Vocal Tract Growth, Motor Control Development, and Vowel Production At the anatomical level, cineradiographic (Goldstein, 1980) and MRI data (Callan, Kent, Guenther, & Vorperian, 2000; Fitch & Giedd, 1999; Vorperian et al., 2005) have shown that the adult vocal apparatus is the result of a complex remodeling of the infant tract. At birth, the overall vocal tract, determined from the larynx to the lips, is approximately 8 cm long, whereas the adult male vocal tract is 17 cm long (Goldstein, 1980). According to Goldstein (1980), the pharynx/oral cavity ratio changes in terms of length from 0.5 at birth to 1.1 in adulthood for a male. Therefore, while the infants’ pharyngeal cavity is much shorter than the oral cavity at birth, it is longer than the front cavity in adults (Fitch & Giedd, 1999). Various studies (Callan et al., 2000; Menard, Schwartz, & Boe, 2004) have reported on the impact of these major anatomical modifications on speakers’ productions of vowels at different developmental stages. For instance, Buhr (1980) suggested that the lack of [u]-like productions in infants’ vowel inventory is related to the small size of their pharyngeal cavity. In addition to the non-uniformity of infants’ anatomical growth, the emergence of vocalic sounds is constrained by limited speech motor abilities in the first year of life (Davis & MacNeilage, 1995; Kent, 1976; Vilain, Abry, Badin, & Brosda, 1999). One main hypothesis is that consonant- and vowel-like sounds are produced with the tongue and the lips being passively raised and lowered via rhythmic motions of the jaw (MacNeilage & Davis, 1990). In this view, the vowels that do not occur in infants’ early productions are those that cannot be articulated because of a lack of motor control over the tongue that would enable infants to produce tongue movements independent of jaw movements. The production of a wider variety of sounds occurs in late childhood or adolescence with the achievement of adult-like motor control (Kent, 1976; Smith & Zelaznik, 2004; Walsh & Smith, 2002). A few studies have investigated the development of articulatory control in young children. Among them, Green, Moore, Higashikawa, & Steeve (2000) showed that the coordination of lip and jaw movements develops as children grow up with a decrease in trial-to-trial variability indicative of the maturation of the speech production system. A similar pattern was observed by Smith and Zelaznik (2004) in a quantitative investigation of lip and jaw movements in 180 children and adults aged 4 to 22. Cheng, Murdoch, Goozee, and Scott (2007) have investigated tongue-jaw interactions with electromagnetic articulography in 48 subjects aged 6 to 38 during the production of the consonants /t/ and /k/. They observed an increase in synchronization of tongue-tip and jaw movements over time. Tongue-body and jaw movements did not show a similar pattern, but became less variable with age. Results were interpreted as indices of maturation of speech motor control with age. It seems that the acquisition of new controls and their integration into existing ones, such as the integration of tongue movements into already controlled jaw oscillatory movements, enables precision for the diversification of speech-related movements.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.090
GPT teacher head0.371
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations14
Published2011
Admission routes1
Has abstractyes

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