Variability is actively regulated in speech

Tang, Dinglan; Parrell, Benjamin; Niziolek, Caroline A.

doi:10.1101/2021.10.08.462639

Cited by 2 publications

(2 citation statements)

References 41 publications

(57 reference statements)

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“…Unfortunately, for speech articulation, work with experimental manipulations of feedback variability is only just starting to appear (see Tang et al, 2021 ), and the effect of manipulating the inter-trial variability of a specific parameter (e.g., frequency of one or more formants) on sensorimotor adaptation to a separate, predictable perturbation of the same parameter (e.g., a consistent formant shift) remains entirely unexplored. We therefore investigated whether an experimental magnification or attenuation of perceived inter-trial formant variability during speech production (a) leads to compensatory adjustments in produced formant variability, (b) induces changes in the temporal structure of formant adjustments across productions, and (c) affects subsequent auditory-motor learning when the speaker is exposed to a predictable formant-shift perturbation.…”

Section: Introductionmentioning

confidence: 99%

Inter-Trial Formant Variability in Speech Production Is Actively Controlled but Does Not Affect Subsequent Adaptation to a Predictable Formant Perturbation

Wang

Max

2022

Front. Hum. Neurosci.

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Despite ample evidence that speech production is associated with extensive trial-to-trial variability, it remains unclear whether this variability represents merely unwanted system noise or an actively regulated mechanism that is fundamental for maintaining and adapting accurate speech movements. Recent work on upper limb movements suggest that inter-trial variability may be not only actively regulated based on sensory feedback, but also provide a type of workspace exploration that facilitates sensorimotor learning. We therefore investigated whether experimentally reducing or magnifying inter-trial formant variability in the real-time auditory feedback during speech production (a) leads to adjustments in formant production variability that compensate for the manipulation, (b) changes the temporal structure of formant adjustments across productions, and (c) enhances learning in a subsequent adaptation task in which a predictable formant-shift perturbation is applied to the feedback signal. Results show that subjects gradually increased formant variability in their productions when hearing auditory feedback with reduced variability, but subsequent formant-shift adaptation was not affected by either reducing or magnifying the perceived variability. Thus, findings provide evidence for speakers’ active control of inter-trial formant variability based on auditory feedback from previous trials, but–at least for the current short-term experimental manipulation of feedback variability–not for a role of this variability regulation mechanism in subsequent auditory-motor learning.

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Section: Introductionmentioning

confidence: 99%

Inter-Trial Formant Variability in Speech Production Is Actively Controlled but Does Not Affect Subsequent Adaptation to a Predictable Formant Perturbation

Wang

Max

2022

Front. Hum. Neurosci.

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“…Two recent studies found that artificially altering perceived inter-trial formant variability in the auditory feedback resulted in compensatory changes in formant production variability, suggesting that inter-trial variability is actively controlled and regulated [ 95 , 96 ]. In the current FACTS design, the task target noise variable is defined by a configuration file rather than being actively controlled during simulations.…”

Section: Discussionmentioning

confidence: 99%

Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech

et al. 2023

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Upon perceiving sensory errors during movements, the human sensorimotor system updates future movements to compensate for the errors, a phenomenon called sensorimotor adaptation. One component of this adaptation is thought to be driven by sensory prediction errors–discrepancies between predicted and actual sensory feedback. However, the mechanisms by which prediction errors drive adaptation remain unclear. Here, auditory prediction error-based mechanisms involved in speech auditory-motor adaptation were examined via the feedback aware control of tasks in speech (FACTS) model. Consistent with theoretical perspectives in both non-speech and speech motor control, the hierarchical architecture of FACTS relies on both the higher-level task (vocal tract constrictions) as well as lower-level articulatory state representations. Importantly, FACTS also computes sensory prediction errors as a part of its state feedback control mechanism, a well-established framework in the field of motor control. We explored potential adaptation mechanisms and found that adaptive behavior was present only when prediction errors updated the articulatory-to-task state transformation. In contrast, designs in which prediction errors updated forward sensory prediction models alone did not generate adaptation. Thus, FACTS demonstrated that 1) prediction errors can drive adaptation through task-level updates, and 2) adaptation is likely driven by updates to task-level control rather than (only) to forward predictive models. Additionally, simulating adaptation with FACTS generated a number of important hypotheses regarding previously reported phenomena such as identifying the source(s) of incomplete adaptation and driving factor(s) for changes in the second formant frequency during adaptation to the first formant perturbation. The proposed model design paves the way for a hierarchical state feedback control framework to be examined in the context of sensorimotor adaptation in both speech and non-speech effector systems.

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Variability is actively regulated in speech

Cited by 2 publications

References 41 publications

Inter-Trial Formant Variability in Speech Production Is Actively Controlled but Does Not Affect Subsequent Adaptation to a Predictable Formant Perturbation

Inter-Trial Formant Variability in Speech Production Is Actively Controlled but Does Not Affect Subsequent Adaptation to a Predictable Formant Perturbation

Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech

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