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Artykuły w czasopismach na temat „Articulatory data”

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Data publikacji: 6 września 2023

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1

Silva, Samuel, Nuno Almeida, Conceição Cunha, Arun Joseph, Jens Frahm, and António Teixeira. "Data-Driven Critical Tract Variable Determination for European Portuguese." Information 11, no. 10 (2020): 491. http://dx.doi.org/10.3390/info11100491.

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Technologies, such as real-time magnetic resonance (RT-MRI), can provide valuable information to evolve our understanding of the static and dynamic aspects of speech by contributing to the determination of which articulators are essential (critical) in producing specific sounds and how (gestures). While a visual analysis and comparison of imaging data or vocal tract profiles can already provide relevant findings, the sheer amount of available data demands and can strongly profit from unsupervised data-driven approaches. Recent work, in this regard, has asserted the possibility of determining c

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2

Abirami, S., L. Anirudh, and P. Vijayalakshmi. "Silent Speech Interface: An Inversion Problem." Journal of Physics: Conference Series 2318, no. 1 (2022): 012008. http://dx.doi.org/10.1088/1742-6596/2318/1/012008.

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Abstract When conventional acoustic-verbal communication is neither possible or desirable, silent speech interfaces (SSI) rely on biosignals, non-acoustic signals created by the human body during speech production, to facilitate communication. Despite considerable advances in sensing techniques that can be employed to capture these biosignals, majority of them are used under controlled scenarios in laboratories. One such example is Electromagnetic Articulograph (EMA), which monitors articulatory motion. It is expensive with inconvenient wiring and practically not portable in real world. Since

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3

Browman, Catherine P., and Louis Goldstein. "Articulatory gestures as phonological units." Phonology 6, no. 2 (1989): 201–51. http://dx.doi.org/10.1017/s0952675700001019.

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We have argued that dynamically defined articulatory gestures are the appropriate units to serve as the atoms of phonological representation. Gestures are a natural unit, not only because they involve task-oriented movements of the articulators, but because they arguably emerge as prelinguistic discrete units of action in infants. The use of gestures, rather than constellations of gestures as in Root nodes, as basic units of description makes it possible to characterise a variety of language patterns in which gestural organisation varies. Such patterns range from the misorderings of disordered

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4

Wang, Jun, Jordan R. Green, Ashok Samal, and Yana Yunusova. "Articulatory Distinctiveness of Vowels and Consonants: A Data-Driven Approach." Journal of Speech, Language, and Hearing Research 56, no. 5 (2013): 1539–51. http://dx.doi.org/10.1044/1092-4388(2013/12-0030).

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Purpose To quantify the articulatory distinctiveness of 8 major English vowels and 11 English consonants based on tongue and lip movement time series data using a data-driven approach. Method Tongue and lip movements of 8 vowels and 11 consonants from 10 healthy talkers were collected. First, classification accuracies were obtained using 2 complementary approaches: (a) Procrustes analysis and (b) a support vector machine. Procrustes distance was then used to measure the articulatory distinctiveness among vowels and consonants. Finally, the distance (distinctiveness) matrices of different vowel

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5

Kuruvilla-Dugdale, Mili, and Antje S. Mefferd. "Articulatory Performance in Dysarthria: Using a Data-Driven Approach to Estimate Articulatory Demands and Deficits." Brain Sciences 12, no. 10 (2022): 1409. http://dx.doi.org/10.3390/brainsci12101409.

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This study pursued two goals: (1) to establish range of motion (ROM) demand tiers (i.e., low, moderate, high) specific to the jaw (J), lower lip (LL), posterior tongue (PT), and anterior tongue (AT) for multisyllabic words based on the articulatory performance of neurotypical talkers and (2) to identify demand- and disease-specific articulatory performance characteristics in talkers with amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD). J, LL, PT, and AT movements of 12 talkers with ALS, 12 talkers with PD, and 12 controls were recorded using electromagnetic articulography. Ver

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6

M., Dhanalakshmi, Nagarajan T., and Vijayalakshmi P. "Significant sensors and parameters in assessment of dysarthric speech." Sensor Review 41, no. 3 (2021): 271–86. http://dx.doi.org/10.1108/sr-01-2021-0004.

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Purpose Dysarthria is a neuromotor speech disorder caused by neuromuscular disturbances that affect one or more articulators resulting in unintelligible speech. Though inter-phoneme articulatory variations are well captured by formant frequency-based acoustic features, these variations are expected to be much higher for dysarthric speakers than normal. These substantial variations can be well captured by placing sensors in appropriate articulatory position. This study focuses to determine a set of articulatory sensors and parameters in order to assess articulatory dysfunctions in dysarthric sp

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7

Byrd, Dani, Edward Flemming, Carl Andrew Mueller, and Cheng Cheng Tan. "Using Regions and Indices in EPG Data Reduction." Journal of Speech, Language, and Hearing Research 38, no. 4 (1995): 821–27. http://dx.doi.org/10.1044/jshr.3804.821.

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This note describes how dynamic electropalatography (EPG) can be used for the acquisition and analysis of articulatory data. Various data reduction procedures developed to analyze the electropalatographic data are reported. Specifically, these procedures concern two interesting areas in EPG data analysis—first, the novel use of speaker-specific articulatory regions and second, the development of arithmetic indices to quantify time-varying articulatory behavior and reflect reduction and coarticulation.

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8

Lee, Jimin, Michael Bell, and Zachary Simmons. "Articulatory Kinematic Characteristics Across the Dysarthria Severity Spectrum in Individuals With Amyotrophic Lateral Sclerosis." American Journal of Speech-Language Pathology 27, no. 1 (2018): 258–69. http://dx.doi.org/10.1044/2017_ajslp-16-0230.

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Purpose The current study investigated whether articulatory kinematic patterns can be extrapolated across the spectrum of dysarthria severity in individuals with amyotrophic lateral sclerosis (ALS). Method Temporal and spatial articulatory kinematic data were collected using electromagnetic articulography from 14 individuals with dysarthria secondary to ALS and 6 typically aging speakers. Speech intelligibility and speaking rate were used as indices of severity. Results Temporal measures (duration, speed of articulators) were significantly correlated with both indices of severity. In speakers

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9

Stevens, Kenneth N. "Inferring articulatory movements from acoustic data." Journal of the Acoustical Society of America 93, no. 4 (1993): 2416. http://dx.doi.org/10.1121/1.405910.

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10

Baum, Shari R., David H. McFarland, and Mai Diab. "Compensation to articulatory perturbation: Perceptual data." Journal of the Acoustical Society of America 99, no. 6 (1996): 3791–94. http://dx.doi.org/10.1121/1.414996.

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11

Kim, Hyunsoon. "The place of articulation of the Korean plain affricate in intervocalic position: an articulatory and acoustic study." Journal of the International Phonetic Association 31, no. 2 (2001): 229–57. http://dx.doi.org/10.1017/s0025100301002055.

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The place of articulation of the Korean plain affricate /c/ and the obstruents /t, s/ is articulatorily and acoustically examined in the intervocalic positions /a―a, a―i, a―u/ taken from four subjects in three dialects. The articulatory data of direct palatograms and linguograms have shown that in these contexts, the plain affricate is not post-alveolar as usually assumed in the literature, but alveolar, just like the alveolar consonants /t, s/, despite some speaker variation regarding the active articulator (tip, blade, anterodorsum). The examination of LPC data has also shown that the affric

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12

Rong, Panying. "Neuromotor Control of Speech and Speechlike Tasks: Implications From Articulatory Gestures." Perspectives of the ASHA Special Interest Groups 5, no. 5 (2020): 1324–38. http://dx.doi.org/10.1044/2020_persp-20-00070.

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Purpose This study aimed to provide a preliminary examination of the articulatory control of speech and speechlike tasks based on a gestural framework and identify shared and task-specific articulatory factors in speech and speechlike tasks. Method Ten healthy participants performed two speechlike tasks (i.e., alternating motion rate [AMR] and sequential motion rate [SMR]) and three speech tasks (i.e., reading of “clever Kim called the cat clinic” at the regular, fast, and slow rates) that varied in phonological complexity and rate. Articulatory kinematics were recorded using an electromagneti

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13

Lucero, Jorge C., and Anders Lofqvist. "Studying articulatory variability using functional data analysis." Journal of the Acoustical Society of America 112, no. 5 (2002): 2417. http://dx.doi.org/10.1121/1.4779885.

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14

Delmoral, Jessica C., Sandra M. Rua Ventura, and João Manuel RS Tavares. "Segmentation of tongue shapes during vowel production in magnetic resonance images based on statistical modelling." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 232, no. 3 (2018): 271–81. http://dx.doi.org/10.1177/0954411917751000.

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Quantification of the anatomic and functional aspects of the tongue is pertinent to analyse the mechanisms involved in speech production. Speech requires dynamic and complex articulation of the vocal tract organs, and the tongue is one of the main articulators during speech production. Magnetic resonance imaging has been widely used in speech-related studies. Moreover, the segmentation of such images of speech organs is required to extract reliable statistical data. However, standard solutions to analyse a large set of articulatory images have not yet been established. Therefore, this article

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15

Chang, Edward F., Garret Kurteff, John P. Andrews, et al. "Pure Apraxia of Speech After Resection Based in the Posterior Middle Frontal Gyrus." Neurosurgery 87, no. 3 (2020): E383—E389. http://dx.doi.org/10.1093/neuros/nyaa002.

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Abstract BACKGROUND AND IMPORTANCE Apraxia of speech is a disorder of articulatory coordination and planning in speech sound production. Its diagnosis is based on deficits in articulation, prosody, and fluency. It is often described concurrent with aphasia or dysarthria, while pure apraxia of speech is a rare entity. CLINICAL PRESENTATION A right-handed man underwent focal surgical resection of a recurrent grade III astrocytoma in the left hemisphere dorsal premotor cortex located in the posterior middle frontal gyrus. After the procedure, he experienced significant long-term speech production

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16

Jiang, Jintao, Abeer Alwan, Patricia Keating, Lynne E. Bernstein, and Edward Auer. "On the correlation between articulatory and acoustic data." Journal of the Acoustical Society of America 108, no. 5 (2000): 2508. http://dx.doi.org/10.1121/1.4743268.

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Wang, Jun, Ashok Samal, Jordan Green, and Tom Carrell. "Vowel recognition from articulatory position time‐series data." Journal of the Acoustical Society of America 125, no. 4 (2009): 2498. http://dx.doi.org/10.1121/1.4783353.

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18

Aryal, Sandesh, and Ricardo Gutierrez-Osuna. "Data driven articulatory synthesis with deep neural networks." Computer Speech & Language 36 (March 2016): 260–73. http://dx.doi.org/10.1016/j.csl.2015.02.003.

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Teplansky, Kristin J., Alan Wisler, Jordan R. Green, Daragh Heitzman, Sara Austin, and Jun Wang. "Measuring Articulatory Patterns in Amyotrophic Lateral Sclerosis Using a Data-Driven Articulatory Consonant Distinctiveness Space Approach." Journal of Speech, Language, and Hearing Research 66, no. 8S (2023): 3076–88. http://dx.doi.org/10.1044/2022_jslhr-22-00320.

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Purpose: The aim of this study was to leverage data-driven approaches, including a novel articulatory consonant distinctiveness space (ACDS) approach, to better understand speech motor control in amyotrophic lateral sclerosis (ALS). Method: Electromagnetic articulography was used to record tongue and lip movement data during the production of 10 consonants from healthy controls ( n = 15) and individuals with ALS ( n = 47). To assess phoneme distinctness, speech data were analyzed using two classification algorithms, Procrustes matching (PM) and support vector machine (SVM), and the area/volume

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20

Shellikeri, Sanjana, Reeman Marzouqah, Benjamin Rix Brooks, Lorne Zinman, Jordan R. Green, and Yana Yunusova. "Psychometric Properties of Rapid Word-Based Rate Measures in the Assessment of Bulbar Amyotrophic Lateral Sclerosis: Comparisons With Syllable-Based Rate Tasks." Journal of Speech, Language, and Hearing Research 64, no. 11 (2021): 4178–91. http://dx.doi.org/10.1044/2021_jslhr-21-00038.

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Purpose Rapid maximum performance repetition tasks have increasingly demonstrated their utility as clinimetric markers supporting diagnosis and monitoring of bulbar disease in amyotrophic lateral sclerosis (ALS). A recently developed protocol uses novel real-word repetitions instead of traditional nonword/syllable sequences in hopes of improving sensitivity to motor speech impairments by adding a phonological target constraint that would activate a greater expanse of the motor speech neuroanatomy. This study established the psychometric properties of this novel clinimetric protocol in its asse

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21

Munhall, K. G., and J. A. Jones. "Articulatory evidence for syllabic structure." Behavioral and Brain Sciences 21, no. 4 (1998): 524–25. http://dx.doi.org/10.1017/s0140525x98391268.

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Because the evolution of speech production is beyond our expertise (and perhaps beyond everyone's expertise) we restrict our comments to areas in which data actually exist. We provide articulatory evidence consistent with the claims made about syllable structure in adult speech and infant babbling, but we also voice some disagreement about speech errors and the typing data.

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Byrd, Dani. "A Phase Window Framework for Articulatory Timing." Phonology 13, no. 2 (1996): 139–69. http://dx.doi.org/10.1017/s0952675700002086.

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One of the most significant challenges in the study of speech production is to acquire a theoretical understanding of how speakers coordinate articulatory movements. A variety of work has demonstrated that articulatory, prosodic and extralinguistic factors all influence speech timing in a complex and interactive way. Models such as Articulatory Phonology that stipulate the relative timing of articulatory units must be revised to allow for this variability. Such a revision is outlined below.The following work should be viewed as a presentation of a new framework for conceptualising articulatory

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23

Perrier, Pascal, and Susanne Fuchs. "Speed–Curvature Relations in Speech Production Challenge the 1/3 Power Law." Journal of Neurophysiology 100, no. 3 (2008): 1171–83. http://dx.doi.org/10.1152/jn.01116.2007.

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Relations between tangential velocity and trajectory curvature are analyzed for tongue movements during speech production in the framework of the 1/3 power law, discovered by Viviani and colleagues for arm movements. In 2004, Tasko and Westbury found for American English that the power function provides a good account of speech kinematics, but with an exponent that varies across articulators. The present work aims at broadening Tasko and Westbury's study 1) by analyzing speed–curvature relations for various languages (French, German, Mandarin) and for a biomechanical tongue model simulating sp

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Lee, Sungbok, Dani Byrd, and Jelena Krivokapić. "Functional data analysis of prosodic effects on articulatory timing." Journal of the Acoustical Society of America 119, no. 3 (2006): 1666–71. http://dx.doi.org/10.1121/1.2161436.

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McGowan, Richard S., and Philip E. Rubin. "Perceptual evaluation of articulatory movement recovered from acoustic data." Journal of the Acoustical Society of America 96, no. 5 (1994): 3328. http://dx.doi.org/10.1121/1.410732.

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Collins, Michael J., Stanley C. Ahalt, and Ashok K. Krishnamurthy. "Generating gestural scores from articulatory data using temporal decomposition." Journal of the Acoustical Society of America 97, no. 5 (1995): 3246. http://dx.doi.org/10.1121/1.411696.

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Kröger, Bernd J., Georg Schröder, and Claudia Opgen‐Rhein. "A gesture‐based dynamic model describing articulatory movement data." Journal of the Acoustical Society of America 98, no. 4 (1995): 1878–89. http://dx.doi.org/10.1121/1.413374.

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Aron, Michaël, Marie-Odile Berger, Erwan Kerrien, Brigitte Wrobel-Dautcourt, Blaise Potard, and Yves Laprie. "Multimodal acquisition of articulatory data: Geometrical and temporal registration." Journal of the Acoustical Society of America 139, no. 2 (2016): 636–48. http://dx.doi.org/10.1121/1.4940666.

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Collins, M. J., A. K. Krishnamurthy, and S. C. Ahalt. "Generating gestural scores from articulatory data using temporal decomposition." IEEE Transactions on Speech and Audio Processing 7, no. 2 (1999): 230–33. http://dx.doi.org/10.1109/89.748129.

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Schmidt, Anna Marie. "Korean to English articulatory mapping: Palatometric and acoustic data." Journal of the Acoustical Society of America 95, no. 5 (1994): 2820–21. http://dx.doi.org/10.1121/1.409681.

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Nam, Hosung, Vikramjit Mitra, Mark K. Tiede, et al. "A procedure for estimating gestural scores from articulatory data." Journal of the Acoustical Society of America 127, no. 3 (2010): 1851. http://dx.doi.org/10.1121/1.3384376.

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Bultena, Sybrine. "Are You in English Gear?" Toegepaste Taalwetenschap in Artikelen 79 (January 1, 2008): 9–20. http://dx.doi.org/10.1075/ttwia.79.02bul.

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It is assumed that the overall combination of the positioning of speech articulators such as the tongue, jaws and lips differs per language, which is commonly referred to as articulatory settings. Previous studies involving analytic listening, as well as acoustic analyses and those based on modern scanning techniques that can visualize the vocal tract claim to have found evidence for the existence of articulatory settings; yet, thus far none of these seems to have found unambiguous measurable evidence for language specific settings. The present study attempts to acoustically measure difference

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Silva, Adelaide H. P., and André Nogueira Xavier. "Libras and Articulatory Phonology." Gradus - Revista Brasileira de Fonologia de Laboratório 3, no. 1 (2018): 103–24. http://dx.doi.org/10.47627/gradus.v3i1.121.

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This paper proposes a new approach to the phonological representation of Brazilian Sign Language (Libras). We depart from the observation that traditional analyses have overlooked features of signed languages which have no (exact) correspondence in spoken languages. Moreover, traditional approaches impose spoken language theoretical constructs on signed languages analyses and, by doing so, they disregard the possibility that signed languages follow different principles, as well as that analytical categories for spoken languages may be inaccurate for signed languages. Therefore, we argue that a

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Thies, Tabea, Doris Mücke, Richard Dano, and Michael T. Barbe. "Levodopa-Based Changes on Vocalic Speech Movements during Prosodic Prominence Marking." Brain Sciences 11, no. 5 (2021): 594. http://dx.doi.org/10.3390/brainsci11050594.

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The present study investigates speech changes in Parkinson’s disease on the acoustic and articulatory level with respect to prosodic prominence marking. To display movements of the underlying articulators, speech data from 16 patients with Parkinson’s disease were recorded using electromagnetic articulography. Speech tasks focused on strategies of prominence marking. Patients’ ability to encode prominence in the laryngeal and supra-laryngeal domain is tested in two conditions to examine the influence of motor performance on speech production further: without dopaminergic medication and with do

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Serrurier, Antoine, and Christiane Neuschaefer-Rube. "Morphological and acoustic modeling of the vocal tract." Journal of the Acoustical Society of America 153, no. 3 (2023): 1867–86. http://dx.doi.org/10.1121/10.0017356.

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In speech production, the anatomical morphology forms the substrate on which the speakers build their articulatory strategy to reach specific articulatory-acoustic goals. The aim of this study is to characterize morphological inter-speaker variability by building a shape model of the full vocal tract including hard and soft structures. Static magnetic resonance imaging data from 41 speakers articulating altogether 1947 phonemes were considered, and the midsagittal articulator contours were manually outlined. A phoneme-independent average-articulation representative of morphology was calculated

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Siriwardena, Yashish M., Nadee Seneviratne, and Carol Espy-Wilson. "Emotion recognition with speech articulatory coordination features." Journal of the Acoustical Society of America 150, no. 4 (2021): A358. http://dx.doi.org/10.1121/10.0008586.

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Mental health illnesses like Major Depressive Disorder and Schizophrenia affect the coordination between articulatory gestures in speech production. Coordination features derived from Vocal tract variables (TVs) predicted by a speech inversion system can quantify the changes in articulatory gestures and have proven to be effective in the classification of mental health disorders. In this study we use data from the IEMOCAP (acted emotions) and MSP Podcast (natural emotions) datasets to understand how coordination features extracted from TVs can be used to capture changes between different emoti

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Ren, Guofeng, Jianmei Fu, Guicheng Shao, and Yanqin Xun. "Articulatory-to-Acoustic Conversion of Mandarin Emotional Speech Based on PSO-LSSVM." Complexity 2021 (January 31, 2021): 1–10. http://dx.doi.org/10.1155/2021/8876005.

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The production of emotional speech is determined by the movement of the speaker’s tongue, lips, and jaw. In order to combine articulatory data and acoustic data of speakers, articulatory-to-acoustic conversion of emotional speech has been studied. In this paper, parameters of LSSVM model have been optimized using the PSO method, and the optimized PSO-LSSVM model was applied to the articulatory-to-acoustic conversion. The root mean square error (RMSE) and mean Mel-cepstral distortion (MMCD) have been used to evaluate the results of conversion; the evaluated result illustrates that MMCD of MFCC

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Gibbon, Fiona E., and Alice Lee. "Using EPG data to display articulatory separation for phoneme contrasts." Clinical Linguistics & Phonetics 25, no. 11-12 (2011): 1014–21. http://dx.doi.org/10.3109/02699206.2011.601393.

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Hutchins, Sandra E. "Method and apparatus for determining articulatory parameters from speech data." Journal of the Acoustical Society of America 91, no. 6 (1992): 3594. http://dx.doi.org/10.1121/1.402800.

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Laprie, Yves. "An articulatory model of the velum developed from cineradiographic data." Journal of the Acoustical Society of America 137, no. 4 (2015): 2269. http://dx.doi.org/10.1121/1.4920288.

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Gonzalez, Jose A., Lam A. Cheah, Angel M. Gomez, et al. "Direct Speech Reconstruction From Articulatory Sensor Data by Machine Learning." IEEE/ACM Transactions on Audio, Speech, and Language Processing 25, no. 12 (2017): 2362–74. http://dx.doi.org/10.1109/taslp.2017.2757263.

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Mooshammer, Christine R., Louis Goldstein, Mark Tiede, Manisha Kulshreshtha, Scott McClure, and Argyro Katsika. "Planning time effects of phonological competition: Articulatory and acoustic data." Journal of the Acoustical Society of America 125, no. 4 (2009): 2657. http://dx.doi.org/10.1121/1.4784180.

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Badino, Leonardo, Claudia Canevari, Luciano Fadiga, and Giorgio Metta. "Integrating articulatory data in deep neural network-based acoustic modeling." Computer Speech & Language 36 (March 2016): 173–95. http://dx.doi.org/10.1016/j.csl.2015.05.005.

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Kröger, Bernd J., Julia Gotto, Susanne Albert, and Christiane Neuschaefer-Rube. "visual articulatory model and its application to therapy of speech disorders: a pilot study." ZAS Papers in Linguistics 40 (January 1, 2005): 79–94. http://dx.doi.org/10.21248/zaspil.40.2005.259.

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A visual articulatory model based on static MRI-data of isolated sounds and its application in therapy of speech disorders is described. The model is capable of generating video sequences of articulatory movements or still images of articulatory target positions within the midsagittal plane. On the basis of this model (1) a visual stimulation technique for the therapy of patients suffering from speech disorders and (2) a rating test for visual recognition of speech movements was developed. Results indicate that patients produce recognition rates above level of chance already without any traini

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Cuzzocrea, Alfredo, Enzo Mumolo, and Giorgio Mario Grasso. "An Effective and Efficient Genetic-Fuzzy Algorithm for Supporting Advanced Human-Machine Interfaces in Big Data Settings." Algorithms 13, no. 1 (2019): 13. http://dx.doi.org/10.3390/a13010013.

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In this paper we describe a novel algorithm, inspired by the mirror neuron discovery, to support automatic learning oriented to advanced man-machine interfaces. The algorithm introduces several points of innovation, based on complex metrics of similarity that involve different characteristics of the entire learning process. In more detail, the proposed approach deals with an humanoid robot algorithm suited for automatic vocalization acquisition from a human tutor. The learned vocalization can be used to multi-modal reproduction of speech, as the articulatory and acoustic parameters that compos

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Albuquerque, Luciana, Ana Rita Valente, Fábio Barros, et al. "Exploring the Age Effects on European Portuguese Vowel Production: An Ultrasound Study." Applied Sciences 12, no. 3 (2022): 1396. http://dx.doi.org/10.3390/app12031396.

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For aging speech, there is limited knowledge regarding the articulatory adjustments underlying the acoustic findings observed in previous studies. In order to investigate the age-related articulatory differences in European Portuguese (EP) vowels, the present study analyzes the tongue configuration of the nine EP oral vowels (isolated context and pseudoword context) produced by 10 female speakers of two different age groups (young and old). From the tongue contours automatically segmented from the US images and manually revised, the parameters (tongue height and tongue advancement) were extrac

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Kuruvilla-Dugdale, Mili, Claire Custer, Lindsey Heidrick, Richard Barohn, and Raghav Govindarajan. "A Phonetic Complexity-Based Approach for Intelligibility and Articulatory Precision Testing: A Preliminary Study on Talkers With Amyotrophic Lateral Sclerosis." Journal of Speech, Language, and Hearing Research 61, no. 9 (2018): 2205–14. http://dx.doi.org/10.1044/2018_jslhr-s-17-0462.

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Purpose This study describes a phonetic complexity-based approach for speech intelligibility and articulatory precision testing using preliminary data from talkers with amyotrophic lateral sclerosis. Method Eight talkers with amyotrophic lateral sclerosis and 8 healthy controls produced a list of 16 low and high complexity words. Sixty-four listeners judged the samples for intelligibility, and 2 trained listeners completed phoneme-level analysis to determine articulatory precision. To estimate percent intelligibility, listeners orthographically transcribed each word, and the transcriptions wer

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Campbell, Jessica, Dani Byrd, and Louis Goldstein. "Frequency stability of articulatory and acoustic modulation functions." Journal of the Acoustical Society of America 152, no. 4 (2022): A288. http://dx.doi.org/10.1121/10.0016304.

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During speech perception, neural activity entrains with moments of high acoustic change. For example, periods of high change in speech amplitude envelope magnitude are tracked by neurons in the human superior temporal gyrus. However, it is unknown whether neural entrainment may also be driven by modulation in the articulatory domain. To locate periods of high articulatory change, a spatiotemporal modulation function (Goldstein, 2019) that quantifies change over time in global vocal tract posture can be used to investigate the potential for such entrainment. Here, the frequency patterning and s

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Dugan, Sarah, Sarah R. Li, Kathryn Eary, et al. "Articulatory response to delayed and real-time feedback based on regional tongue displacements." Journal of the Acoustical Society of America 152, no. 4 (2022): A199. http://dx.doi.org/10.1121/10.0016021.

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Speech is one of the most complex motor tasks, due to its rapid timing and necessary precision. The difficulty of measuring articulatory movement in real time has made it difficult to investigate motion-based biofeedback for speech. Previously, we demonstrated the use of an automatic measure of tongue movement accuracy from ultrasound imaging. Using this measure for articulatory biofeedback in a simplified, game-like display may benefit the learning of speech movement patterns. To better understand real-time articulatory biofeedback and improve the design of this display, this study presented

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Richmond, Korin, Zhenhua Ling, and Junichi Yamagishi. "The use of articulatory movement data in speech synthesis applications: An overview — Application of articulatory movements using machine learning algorithms —." Acoustical Science and Technology 36, no. 6 (2015): 467–77. http://dx.doi.org/10.1250/ast.36.467.

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