Taxonomies in Biology, Phonetics, Phonology, and Speech Motor Control

1990 ◽  
Vol 55 (4) ◽  
pp. 596-611 ◽  
Author(s):  
John W. Folkins ◽  
Ken M. Bleile
Keyword(s):  
Motor Control ◽  
Motor Performance ◽  
Motor System ◽  
Motor Deficits ◽  
Speech Motor Control ◽  
Phonetic Transcription ◽  
Phonological Deficits ◽  
And Performance ◽  
Speech Motor

This article begins with a review explaining the different purposes of biological taxonomies. Taxonomic units are often dependent on the purpose for which the taxonomy has been constructed. Biological taxonomies provide an analogy that we use to emphasize some of the distinctions among the units of phonetic transcription systems, competence phonologies, and performance phonologies. The units of both phonology and phonetic transcription are considered as possible units of the speech motor system, and some of the difficulties of this assumption are explained. Although phonemic units, like units of phonetic transcription, are useful for many purposes, it is not theoretically necessary to use units derived as part of competence phonologies in systems attempting to explain phonological performance or speech motor performance. In this regard, we challenge the concept of coarticulation, because it is based on assumptions about the role of phonological or phonetic units in speech motor control. We offer an integrated perspective that has implications for research in speech motor control and deficits of the speech motor system. We see speech motor deficits as distinct from, yet possibly interacting with, phonological deficits.

scholarly journals Modeling the Role of Sensory Feedback in Speech Motor Control and Learning

2019 ◽  
Vol 62 (8S) ◽  
pp. 2963-2985 ◽  
Author(s):  
Benjamin Parrell ◽  
John Houde
Keyword(s):  
Motor Control ◽  
Motor System ◽  
Sensory Feedback ◽  
Computational Models ◽  
State Feedback Control ◽  
Speech Motor Control ◽  
Control Feedback ◽  
Motor Production ◽  
Speech Motor

Purpose While the speech motor system is sensitive to feedback perturbations, sensory feedback does not seem to be critical to speech motor production. How the speech motor system is able to be so flexible in its use of sensory feedback remains an open question. Method We draw on evidence from a variety of disciplines to summarize current understanding of the sensory systems' role in speech motor control, including both online control and motor learning. We focus particularly on computational models of speech motor control that incorporate sensory feedback, as these models provide clear encapsulations of different theories of sensory systems' function in speech production. These computational models include the well-established directions into velocities of articulators model and computational models that we have been developing in our labs based on the domain-general theory of state feedback control (feedback aware control of tasks in speech model). Results After establishing the architecture of the models, we show that both the directions into velocities of articulators and state feedback control/feedback aware control of tasks models can replicate key behaviors related to sensory feedback in the speech motor system. Although the models agree on many points, the underlying architecture of the 2 models differs in a few key ways, leading to different predictions in certain areas. We cover key disagreements between the models to show the limits of our current understanding and point toward areas where future experimental studies can resolve these questions. Conclusions Understanding the role of sensory information in the speech motor system is critical to understanding speech motor production and sensorimotor learning in healthy speakers as well as in disordered populations. Computational models, with their concrete implementations and testable predictions, are an important tool to understand this process. Comparison of different models can highlight areas of agreement and disagreement in the field and point toward future experiments to resolve important outstanding questions about the speech motor control system.

scholarly journals Abnormal Speech Motor Control in Individuals with 16p11.2 Deletions

2017 ◽  
Author(s):  
Carly Demopoulos ◽  
Hardik Kothare ◽  
Danielle Mizuiri ◽  
Jennifer Henderson-Sabes ◽  
Brieana Fregeau ◽  
...  
Keyword(s):  
Motor Control ◽  
Auditory Feedback ◽  
Spectral Peak ◽  
Motor Deficits ◽  
Speech Motor Control ◽  
Sensorimotor Adaptation ◽  
Speech And Language ◽  
Vowel Production ◽  
Identity Changes ◽  
Speech Motor

AbstractSpeech and motor deficits are highly prevalent (>70%) in individuals with the 600 kb BP4-BP5 16p11.2 deletion; however, the mechanisms that drive these deficits are unclear, limiting our ability to target interventions and advance treatment. This study examined fundamental aspects of speech motor control in participants with the 16p11.2 deletion. To assess capacity for control of voice, we examined how accurately and quickly subjects changed the pitch of their voice within a trial to correct for a transient perturbation of the pitch of their auditory feedback. When compared to sibling controls, 16p11.2 deletion carriers show an over-exaggerated pitch compensation response to unpredictable mid-vocalization pitch perturbations. We also examined sensorimotor adaptation of speech by assessing how subjects learned to adapt their sustained productions of formants (speech spectral peak frequencies important for vowel identity), in response to consistent changes in their auditory feedback during vowel production. Deletion carriers show reduced sensorimotor adaptation to sustained vowel identity changes in auditory feedback. These results together suggest that 16p11.2 deletion carriers have fundamental impairments in the basic mechanisms of speech motor control and these impairments may partially explain the deficits in speech and language in these individuals.

Do We Have a “Mental Syllabary” in the Brain? An fMRI Study

Motor Control ◽  
2011 ◽  
Vol 15 (1) ◽  
pp. 34-51 ◽  
Author(s):  
Bettina Brendel ◽  
Michael Erb ◽  
Axel Riecker ◽  
Wolfgang Grodd ◽  
Hermann Ackermann ◽  
...  
Keyword(s):  
Motor Control ◽  
Low Frequency ◽  
Frequency Effect ◽  
Speech Motor Control ◽  
Motor Execution ◽  
Syllable Frequency ◽  
Fmri Study ◽  
The Brain ◽  
Speech Motor

The present study combines functional magnetic resonance imaging (fMRI) and reaction time (RT) measurements to further elucidate the influence of syllable frequency and complexity on speech motor control processes, i.e., overt reading of pseudowords. Tying in with a recent fMRI-study of our group we focused on the concept of a mental syllabary housing syllable sized ready-made motor plans for high- (HF), but not low-frequency (LF) syllables. The RT-analysis disclosed a frequency effect weakened by a simultaneous complexity effect for HF-syllables. In contrast, the fMRI data revealed no effect of syllable frequency, but point to an impact of syllable structure: Compared with CV-items, syllables with a complex onset (CCV) yielded higher hemodynamic activation in motor “execution” areas (left sensorimotor cortex, right inferior cerebellum), which is at least partially compatible with our previous study. We discuss the role of the syllable in speech motor control.

A Contribution to the Role of the Claustrum in Speech Motor Control Processes

2021 ◽  
Author(s):  
Manfred Pützer ◽  
Jean Richard Moringlane ◽  
Wolfgang Reith ◽  
Christoph M. Krick
Keyword(s):  
Motor Control ◽  
Speech Motor Control ◽  
Control Processes ◽  
Speech Motor

scholarly journals Knockout of Foxp2 disrupts vocal development in mice

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Gregg A. Castellucci ◽  
Matthew J. McGinley ◽  
David A. McCormick
Keyword(s):  
Motor Control ◽  
Model System ◽  
Courtship Song ◽  
Vocal Behavior ◽  
Speech Motor Control ◽  
Vocal Development ◽  
Rhythmic Structure ◽  
Adult Mice ◽  
Speech Motor

Abstract The FOXP2 gene is important for the development of proper speech motor control in humans. However, the role of the gene in general vocal behavior in other mammals, including mice, is unclear. Here, we track the vocal development of Foxp2 heterozygous knockout (Foxp2+/−) mice and their wildtype (WT) littermates from juvenile to adult ages, and observe severe abnormalities in the courtship song of Foxp2+/− mice. In comparison to their WT littermates, Foxp2+/− mice vocalized less, produced shorter syllable sequences, and possessed an abnormal syllable inventory. In addition, Foxp2+/− song also exhibited irregular rhythmic structure, and its development did not follow the consistent trajectories observed in WT vocalizations. These results demonstrate that the Foxp2 gene is critical for normal vocal behavior in juvenile and adult mice, and that Foxp2 mutant mice may provide a tractable model system for the study of the gene’s role in general vocal motor control.

How the Study of Speech Motor Control Can Inform Assessment and Intervention in Childhood Apraxia of Speech

2020 ◽  
Vol 5 (4) ◽  
pp. 784-793 ◽  
Author(s):  
Julie Case ◽  
Maria Grigos
Keyword(s):  
Motor Control ◽  
Task Complexity ◽  
Past Research ◽  
Theory And Practice ◽  
Motor Deficits ◽  
Speech Motor Control ◽  
Clinical Implications ◽  
Apraxia Of Speech ◽  
Childhood Apraxia Of Speech ◽  
Speech Motor

Purpose The study of speech motor control has led to great advancements in the current understanding of childhood apraxia of speech (CAS). There remains a significant need to bridge the gap between theory and practice to fully understand the clinical implications of past research. Method This review article reviews the speech motor control research in CAS and discusses how these works have offered key information about the underlying motor deficits (Grigos et al., 2015; Terband et al., 2019), the influence of structured practice on speech performance (Case & Grigos, 2016; Grigos & Case, 2018), and the role of task complexity (Case, 2019; Case & Grigos, 2016; Grigos & Case, 2018). We highlight salient points from this existing literature and clinical implications to the assessment and treatment of CAS. Conclusion The study of speech motor control has shed light on a number of key factors related to CAS. Even within perceptually accurate speech, children with CAS display differences in movement patterning and timing control. Assessment must aim to more directly tax speech motor skills to obtain a thorough and accurate illustration of production deficits. Intervention is challenged with the task of not only improving production accuracy but also facilitating more efficient motor planning and programming. Motor-based intervention that applies motor learning principles and introduces variability across motor, phonetic, and prosodic contexts is believed to achieve this goal, though research is needed to better understand changes in speech motor control with treatment.

Don’t blame yourself: Conscious source monitoring modulates feedback control during speech production

2020 ◽  
Author(s):  
Matthias K. Franken ◽  
Robert Hartsuiker ◽  
Petter Johansson ◽  
Lars Hall ◽  
Andreas Lind
Keyword(s):  
Motor Control ◽  
Auditory Feedback ◽  
Sensory Feedback ◽  
Source Monitoring ◽  
External Source ◽  
The Self ◽  
Speech Motor Control ◽  
Sensory Event ◽  
Speech Motor

Sensory feedback plays an important role in speech motor control. One of the main sources of evidence for this are studies where online auditory feedback is perturbed during ongoing speech. In motor control, it is therefore crucial to distinguish between sensory feedback and externally generated sensory events. This is called source monitoring. Previous altered feedback studies have taken non-conscious source monitoring for granted, as automatic responses to altered sensory feedback imply that the feedback changes are processed as self-caused. However, the role of conscious source monitoring is unclear. The current study investigated whether conscious source monitoring modulates responses to unexpected pitch changes in auditory feedback. During a first block, some participants spontaneously attributed the pitch shifts to themselves (self-blamers) while others attributed them to an external source (other-blamers). Before block 2, all participants were informed that the pitch shifts were experimentally induced. The self-blamers then showed a reduction in response magnitude in block 2 compared with block 1, while the other-blamers did not. This suggests that conscious source monitoring modulates responses to altered auditory feedback, such that consciously ascribing feedback to oneself leads to larger compensation responses. These results can be accounted for within the dominant comparator framework, where conscious source monitoring could modulate the gain on sensory feedback. Alternatively, the results can be naturally explained from an inferential framework, where conscious knowledge may bias the priors in a Bayesian process to determine the most likely source of a sensory event.

EXPRESS: Don’t blame yourself: Conscious source monitoring modulates feedback control during speech production

2022 ◽  
pp. 174702182210756
Author(s):  
Matthias K. Franken ◽  
Robert J Hartsuiker ◽  
Petter Johansson ◽  
Lars Hall ◽  
Andreas Lind
Keyword(s):  
Motor Control ◽  
Auditory Feedback ◽  
Sensory Feedback ◽  
Source Monitoring ◽  
External Source ◽  
The Self ◽  
Speech Motor Control ◽  
Sensory Event ◽  
Speech Motor

Sensory feedback plays an important role in speech motor control. One of the main sources of evidence for this are studies where online auditory feedback is perturbed during ongoing speech. In motor control, it is therefore crucial to distinguish between sensory feedback and externally generated sensory events. This is called source monitoring. Previous altered feedback studies have taken non-conscious source monitoring for granted, as automatic responses to altered sensory feedback imply that the feedback changes are processed as self-caused. However, the role of conscious source monitoring is unclear. The current study investigated whether conscious source monitoring modulates responses to unexpected pitch changes in auditory feedback. During a first block, some participants spontaneously attributed the pitch shifts to themselves (self-blamers) while others attributed them to an external source (other-blamers). Before block 2, all participants were informed that the pitch shifts were experimentally induced. The self-blamers then showed a reduction in response magnitude in block 2 compared with block 1, while the other-blamers did not. This suggests that conscious source monitoring modulates responses to altered auditory feedback, such that consciously ascribing feedback to oneself leads to larger compensation responses. These results can be accounted for within the dominant comparator framework, where conscious source monitoring could modulate the gain on sensory feedback. Alternatively, the results can be naturally explained from an inferential framework, where conscious knowledge may bias the priors in a Bayesian process to determine the most likely source of a sensory event.

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