Speech communication

Speech Communication, 1997

A theoretical overview and supporting data are presented about the control of the segmental component of speech production. Findings of "motor-equivalent" trading relations between the contributions of two constrictions to the same acoustic transfer function provide preliminary support for the idea that segmental control is based on acoustic or auditory-perceptual goals. The goals are determined partly by non-linear, quanta1 relations (called "saturation effects") between motor commands and articulatory movements and between articulation and sound. Since processing times would be too long to allow the use of auditory feedback for closed-loop error correction in achieving acoustic goals, the control mechanism must use a robust "internal model" of the relation between articulation and the sound output that is learned during speech acquisition. Studies of the speech of cochlear implant and bilateral acoustic neuroma patients provide evidence supporting two roles for auditory feedback in adults: maintenance of the internal model, and monitoring the acoustic environment to help assure intelligibility by guiding relatively rapid adjustments in "postural" parameters underlying average sound level, speaking rate and the amount of prosodically-based inflection of FO and SPL. 0 1997 Elsevier Science B.V.

Journal of Speech, Language, and Hearing Research, 2019

Journal of Memory and Language, 1985

Language and Cognitive Processes, 2013

In this target paper, Hickok proposes a hierarchical state feedback control (HSFC) model of speech production in an attempt to integrate a range of theoretical and empirical works coming from psycholinguistic, motor control, neuropsychology and cognitive neuroscience. While we find much to like about the HSFC model, we will focus in this commentary on one important piece of disagreement, namely, its conceptual view on the nature and control of phoneme in speech production.

Purpose-The authors examined the involvement of 2 speech motor programming processes identified by S. T. Klapp (1995, 2003) during the articulation of utterances differing in syllable and sequence complexity. According to S. T. Klapp, 1 process, INT, resolves the demands of the programmed unit, whereas a second process, SEQ, oversees the serial order demands of longer sequences. Method-A modified reaction time paradigm was used to assess INT and SEQ demands. Specifically, syllable complexity was dependent on syllable structure, whereas sequence complexity involved either repeated or unique syllabi within an utterance. Results-INT execution was slowed when articulating single syllables in the form CCCV compared to simpler CV syllables. Planning unique syllables within a multisyllabic utterance rather than repetitions of the same syllable slowed INT but not SEQ. Conclusions-The INT speech motor programming process, important for mental syllabary access, is sensitive to changes in both syllable structure and the number of unique syllables in an utterance.

Phonetica, 2002

While the existence of the trough effect is unquestioned, its theoretical significance is unknown. A multifaceted instrumental approach – spectrographic, cineradiographic, and vocal tract modeling – was used to document the trough effect in open (V.CV) and closed (VC.V) syllable forms using a symmetrical vowel context surrounding labial stops. Collectively, the results document the trough phenomeon as a momentary deactivation of tongue and/or lip movement after V1 and continuing into the stop closure. This empirical event suggests a segment-by-segment activation pattern as opposed to a diphthongal vowel-to-vowel trajectory with an independent and superimposed consonantal gesture. Quantitative models of VCV coarticulation must incorporate the trough effect in order to more effectively capture the kinematic properties of speech.

2001

A model of the sensorimotor control of speech production is presented. The model is being implemented as a set of computer simulations. It converts an input sequence of discrete phonemes into quasi-continuous motor commands and a sound output. A key feature of the model is that the goals for speech movements, at least for some kinds of sounds, are regions in auditory-temporal space. The model is designed to have properties that are as faithful as possible to data from speakers -including measures of brain function, speech motor control mechanisms, physiology, anatomy, biomechanics and acoustics. Examples of simulations and actual data from some of these domains are presented. The examples demonstrate properties of the model or they are consistent with hypotheses generated from it. Our long-range goal is to implement the model completely and test it exhaustively, in the belief that doing so will significantly advance our understanding of speech motor control.

Brain Research, 2009

A large body of evidence suggests that the motor system maintains a forward model that predicts the sensory outcome of movements. When sensory feedback does not match the predicted consequences, a compensatory response corrects for the motor error and the forward model is updated to prevent future errors. Like other motor behaviours, vocalization relies on sensory feedback for the maintenance of forward models. In this study, we used a frequency altered feedback (FAF) paradigm to study the role of auditory feedback in the control of vocal pitch (F0). We adapted subjects to a one semitone shift and induced a perturbation by briefly removing the altered feedback. This was compared to a control block in which a 1 semitone perturbation was introduced into an unshifted trial, or trials were randomly shifted up 1 semitone, and a perturbation was introduced by removing the feedback alteration. The compensation response to mid-utterance perturbations was identical in all conditions, and was always smaller than the compensation to a shift at utterance onset. These results are explained by a change in the control strategy at utterance onset and mid-utterance. At utterance onset, auditory feedback is compared to feedback predicted by a forward model to ensure the pitch goal is achieved. However, after utterance onset, the control strategy switches and stabilization is maintained by comparing feedback to previous F0 production.

2011