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1. Development of vowel acoustics and subglottal resonances in American English-speaking children: A longitudinal Study

   https://doi.org/10.1121/10.0016294  

   Shetty, Vishwas; Lulich, Steven M.; Palo, Pertti; Alwan, Abeer (October 2022, The Journal of the Acoustical Society of America)

   Acoustic analysis of typically developing elementary school-aged (prepubertal) children’s speech has been primarily performed on cross-sectional data in the past. Few studies have examined longitudinal data in this age group. For this presentation, we analyze the developmental changes in the acoustic properties of children’s speech using data collected longitudinally over four years (from first grade to fourth grade). Four male and four female children participated in this study. Data were collected once every year for each child. Using these data, we measured the four-year development of subglottal acoustics (first two subglottal resonances) and vowel acoustics (first four formants and fundamental frequency). Subglottal acoustic measurements are relatively independent of context, and average values were obtained for each child in each year. Vowel acoustics measurements were made for seven vowels (i, ɪ, ɛ, æ, ʌ, ɑ, u), each occurring in two different words in the stressed syllable. We investigated the correlations between the children’s subglottal acoustics, vowel acoustics, and growth-related variables such as standing height, sitting height, and chronological age. Gender-, vowel-, and child-specific analyses were carried out in order to shed light on how typically developing speech acoustics depend on such variables. [Work supported, in part, by the NSF.] 

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2. Co-speech gestures influence the magnitude and stability of articulatory movements: evidence for coupling-based enhancement

   https://doi.org/10.1038/s41598-024-84097-6  

   Garvin, Karee; Spradling, Eliana; Franich, Kathryn (December 2025, Scientific Reports)

   Humans rarely speak without producing co-speech gestures of the hands, head, and other parts of the body. Co-speech gestures are also highly restricted in how they are timed with speech, typically synchronizing with prosodically-prominent syllables. What functional principles underlie this relationship? Here, we examine how the production of co-speech manual gestures influences spatiotemporal patterns of the oral articulators during speech production. We provide novel evidence that words uttered with accompanying co-speech gestures are produced with more extreme tongue and jaw displacement, and that presence of a co-speech gesture contributes to greater temporal stability of oral articulatory movements. This effect–which we term coupling enhancement–differs from stress-based hyperarticulation in that differences in articulatory magnitude are not vowel-specific in their patterning. Speech and gesture synergies therefore constitute an independent variable to consider when modeling the effects of prosodic prominence on articulatory patterns. Our results are consistent with work in language acquisition and speech-motor control suggesting that synchronizing speech to gesture can entrain acoustic prominence. 

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3. Cross-lingual articulatory feature information transfer for speech recognition using recurrent progressive neural networks

   https://doi.org/10.21437/Interspeech.2022-11202  

   Morshed, Mahir; Hasegawa-Johnson, Mark (September 2022, Proceedings of Interspeech 2022)

   A system for the lateral transfer of information from end-to-end neural networks recognizing articulatory feature classes to similarly structured networks recognizing phone tokens is here proposed. The system connects recurrent layers of feature detectors pre-trained on a base language to recurrent layers of a phone recognizer for a different target language, this inspired primarily by the progressive neural network scheme. Initial experiments used detectors trained on Bengali speech for four articulatory feature classes—consonant place, consonant manner, vowel height, and vowel backness—attached to phone recognizers for four other Asian languages (Javanese, Nepali, Sinhalese, and Sundanese). While these do not currently suggest consistent performance improvements across different low-resource settings for target languages, irrespective of their genealogic or phonological relatedness to Bengali, they do suggest the need for further trials with different language sets, altered data sources and data configurations, and slightly altered network setups. 

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4. How an aglossic speaker produces an alveolar-like percept without a functional tongue tip

   https://doi.org/10.1121/10.0001329  

   Toutios, Asterios; Xu, Melissa; Byrd, Dani; Goldstein, Louis; Narayanan, Shrikanth (June 2020, The Journal of the Acoustical Society of America)

   It has been previously observed [McMicken, Salles, Berg, Vento-Wilson, Rogers, Toutios, and Narayanan. (2017). J. Commun. Disorders, Deaf Stud. Hear. Aids 5(2), 1–6] using real-time magnetic resonance imaging that a speaker with severe congenital tongue hypoplasia (aglossia) had developed a compensatory articulatory strategy where she, in the absence of a functional tongue tip, produced a plosive consonant perceptually similar to /d/ using a bilabial constriction. The present paper provides an updated account of this strategy. It is suggested that the previously observed compensatory bilabial closing that occurs during this speaker's /d/ production is consistent with vocal tract shaping resulting from hyoid raising created with mylohyoid action, which may also be involved in typical /d/ production. Simulating this strategy in a dynamic articulatory synthesis experiment leads to the generation of /d/-like formant transitions. 

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5. Quantitative Acoustic versus Deep Learning Metrics of Lenition

   https://doi.org/10.3390/languages8020098  

   Wayland, Ratree; Tang, Kevin; Wang, Fenqi; Vellozzi, Sophia; Sengupta, Rahul (June 2023, Languages)

   Spanish voiced stops /b, d, ɡ/ surfaced as fricatives [β, ð, ɣ] in intervocalic position due to a phonological process known as spirantization or, more broadly, lenition. However, conditioned by various factors such as stress, place of articulation, flanking vowel quality, and speaking rate, phonetic studies reveal a great deal of variation and gradience of these surface forms, ranging from fricative-like to approximant-like [β⊤, ð⊤, ɣ⊤]. Several acoustic measurements have been used to quantify the degree of lenition, but none is standard. In this study, the posterior probabilities of sonorant and continuant phonological features in a corpus of Argentinian Spanish estimated by a deep learning Phonet model as measures of lenition were compared to traditional acoustic measurements of intensity, duration, and periodicity. When evaluated against known lenition factors: stress, place of articulation, surrounding vowel quality, word status, and speaking rate, the results show that sonorant and continuant posterior probabilities predict lenition patterns that are similar to those predicted by relative acoustic intensity measures and are in the direction expected by the effort-based view of lenition and previous findings. These results suggest that Phonet is a reliable alternative or additional approach to investigate the degree of lenition. 

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