93 research outputs found

    Quand nasal est plus que nasal : L’articulation orale des voyelles nasales en français // When nasal is more than nasal: Oral articulation of French nasal vowels

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    Cet article rend compte des résultats préliminaires de l’étude des articulations linguales et labiales des voyelles orales et nasales de trois locuteurs de français métropolitain (FM) enregistrées avec un système EMA. La variation inter-locuteur des articulations orales des voyelles est interprétée en terme d’équivalence motrice dans la dispersion acoustique des systèmes vocaliques : les locuteurs témoignent des réalisations acoustiques similaires, mais ils utilisent des stratégies articulatoires différentes pour y parvenir. // Lingual and labial articulations of oral and nasal vowels of three Metropolitan French (FM) speakers were recorded using an EMA system. Inter-speaker variation in these oral articulations suggest that the role of motor equivalence is important in the acoustic dispersion of this vowel system: the speakers have a similar acoustic output, but use different articulatory strategies to achieve this output

    An open-source toolbox for measuring vocal tract shape from real-time magnetic resonance images

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    Real-time magnetic resonance imaging (rtMRI) is a technique that provides high-contrast videographic data of human anatomy in motion. Applied to the vocal tract, it is a powerful method for capturing the dynamics of speech and other vocal behaviours by imaging structures internal to the mouth and throat. These images provide a means of studying the physiological basis for speech, singing, expressions of emotion, and swallowing that are otherwise not accessible for external observation. However, taking quantitative measurements from these images is notoriously difficult. We introduce a signal processing pipeline that produces outlines of the vocal tract from the lips to the larynx as a quantification of the dynamic morphology of the vocal tract. Our approach performs simple tissue classification, but constrained to a researcher-specified region of interest. This combination facilitates feature extraction while retaining the domain-specific expertise of a human analyst. We demonstrate that this pipeline generalises well across datasets covering behaviours such as speech, vocal size exaggeration, laughter, and whistling, as well as producing reliable outcomes across analysts, particularly among users with domain-specific expertise. With this article, we make this pipeline available for immediate use by the research community, and further suggest that it may contribute to the continued development of fully automated methods based on deep learning algorithms

    Using naive listener imitations of native speaker productions to investigate mechanisms of listener-based sound change

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    This study was designed to test whether listener-based sound change-listener misperception (Ohala, 1981, 1993) and perceptual cue re-weighting (Beddor, 2009, 2012)-can be observed synchronically in a laboratory setting. Co-registered articulatory data (degree of nasalization, tongue height, breathiness) and acoustic data (F1 frequency) related to the productions of phonemic oral and nasal vowels of Southern French were first collected from four native speakers, and the acoustic recordings were subsequently presented to nine Australian English naive listeners, who were instructed to imitate the native productions. During these imitations, similar articulatory and acoustic data were collected in order to compare the articulatory strategies used by the two groups. The results suggest that the imitators successfully reproduced the acoustic distinctions made by the native speakers, but that they did so using different articulatory strategies. The articulatory strategies for the vowel pair /a/-/a/ suggest that listeners (at least partially) misperceived F1-lowering due to nasalization and breathiness as being due to tongue height. Additional evidence supports perceptual cue re-weighting, in that the naive imitators employed nasalance less, and tongue height more, in order to obtain the same F1 nasal-oral distinctions that the native speakers had originally produced

    Phonological contrast and phonetic variation: The case of velars in iwaidja

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    2020, Linguistic Society of America. All rights reserved. A field-based ultrasound and acoustic study of Iwaidja, an endangered Australian Aboriginal language, investigates the phonetic identity of nonnasal velar consonants in intervocalic position, where past work has proposed a [+continuant] vs. [−continuant] phonemic contrast. We analyze the putative contrast within a continuous phonetic space, defined by both acoustic and articulatory parameters, and find gradient variation: from more consonantal realizations, such as [ɰ], to more vocalic realizations, such as [a]. The distribution of realizations across lexical items and speakers does not support the proposed phonemic contrast. This case illustrates how lenition that is both phonetically gradient and variable across speakers and words can give the illusion of a contextu-ally restricted phonemic contrast

    An investigation of the dynamics of vowel nasalization in Arabana using machine learning of acoustic features

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    This paper presents exploratory research on temporally dynamic patterns of vowel nasalization from two speakers of Arabana. To derive a dynamic measure of nasality, we use gradient tree boosting algorithms to statistically learn the mapping between acoustics and vowel nasality in a speaker-specific manner. Three primary findings emerge: (1) NVN contexts exhibit nasalization throughout the entirety of the vowel interval, and we propose that a similar co-articulatory realization previously acted to resist diachronic change in this environment; (2) anticipatory vowel nasalization is nearly as extensive as carryover vowel nasalization, which is contrary to previous claims; and (3) the degree of vowel nasalization in word-initial contexts is relatively high, even in the #_C environment, suggesting that the sound change *#Na > #a has involved the loss of the oral constriction associated with N but not the complete loss of the velum gesture

    Analyzing speech in both time and space : generalized additive mixed models can uncover systematic patterns of variation in vocal tract shape in real-time MRI

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    We present a method of using generalized additive mixed models (GAMMs) to analyze midsagittal vocal tract data obtained from real-time magnetic resonance imaging (rt-MRI) video of speech production. Applied to rt-MRI data, GAMMs allow for observation of factor effects on vocal tract shape throughout two key dimensions: time (vocal tract change over the temporal course of a speech segment) and space (location of change within the vocal tract). Examples of this method are provided for rt-MRI data collected at a temporal resolution of 20 ms and a spatial resolution of 1.41 mm, for 36 native speakers of German. The rt-MRI data were quantified as 28-point semi-polar-grid aperture functions. Three test cases are provided as a way of observing vocal tract differences between: (1) /aː/ and /iː/, (2) /aː/ and /aɪ/, and (3) accentuated and unstressed /aː/. The results for each GAMM are independently validated using functional linear mixed models (FLMMs) constructed from data obtained at 20% and 80% of the vowel interval. In each case, the two methods yield similar results. In light of the method similarities, we propose that GAMMs are a robust, powerful, and interpretable method of simultaneously analyzing both temporal and spatial effects in rt-MRI video of speech
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