Feedback modification for reducing stuttering

Background : Ziegler (2003) reviews neural and behavioural evidence to support a task-dependent model of motor control, whereby motor speech disorders represent impairment of a sensory-minor system specialised for speech. Based on this approach, Ziegler argues against the examination of volitional or novel nonspeech motor activities to gain insight into motor control for speech. Aims : The primary objective of this paper is to discuss Ziegler's (2003) conceptualisation of the task-dependent model and present an alternative integrative model. In the latter, speech and volitional nonspeech motor control are integrated into the functioning of a more general motor system where neural and behavioural systems demonstrate areas of overlap. Studies of the nervous system, the evolutionary foundations of speech in great apes, behaviour, and motor learning are presented to support an integrative model of motor control. Main Contribution : Neurological and evolutionary evidence strongly suggest that neural networks are flexible, multifaceted, multifunctional and overlapping in function. It is highly likely that a higher-level behaviour like speech involves networks that are similarly multifunctional and overlapping with other motor functions. Ziegler's concept of task-dependent motor control may relate as much to parameters such as complexity, familiarity, and automaticity of task performance as to the nonpeech-speech distinction. Studies are reviewed that support the inclusion of nonspeech motor tasks in assessment of the disordered speech motor control system. Specific nonspeech tasks clearly facilitate differential diagnosis and provide insight into the functioning breakdown of the motor system for related but more complex speech behaviours. Finally, motor learing studies are discussed with particular reference to how these might inform models of motor control. Conclusions : This response cautions against the seemingly premature acceptance of a model assuming separate sensory motor systems for volitional nonspeech motor activities and speech. Continued research, without the limitations imposed by such an assumption, is required to enhance understanding of component parts of complex behaviours and how those components interact in normal and damaged systems at different levels of a performance. These data have the potential to form the basis for new, more effective approaches to treatment of motor speech disorders.

Talkers are known to compensate only partially for experimentally-induced changes to their auditory feedback. In a typical experiment, talkers might hear their FI feedback shifted higher (so that/epsilon/ sounds like /ae/, for example), and compensate by lowering FI in their subsequent speech by about a quarter of that distance. Here, we sought to characterize and understand partial compensation by examining how talkers respond to each step on a staircase of increasing shifts in auditory feedback. Subjects wore an apparatus which altered their real time auditory feedback. They were asked to repeat visually-presented hVd stimulus words while feedback was altered stepwise over the course of 360 trials. We used a novel analysis method to calculate each subject's compensation at each compensation step relative to their baseline. Results demonstrated that subjects compensated more for small feedback shifts than for larger shifts. We suggest that this pattern is consistent with vowel targets that incorporate auditory and somatosensory information, and a speech motor control system that is driven by differential weighting of auditory and somatosensory feedback.

Neurobiology of speaking and stuttering

Spoken language exists because of a remarkable neural process. Inside a speaker's brain, an intended message gives rise to neural signals activating the muscles of the vocal tract. The process is remarkable because these muscles are activated in just the right way that the vocal tract produces sounds a listener understands as the intended message. What is the best approach to understanding the neural substrate of this crucial motor control process? One of the key recent modeling developments in neuroscience has been the use of state feedback control (SFC) theory to explain the role of the CNS in motor control. SFC postulates that the CNS controls motor output by (1) estimating the current dynamic state of the thing (e.g., arm) being controlled, and (2) generating controls based on this estimated state. SFC has successfully predicted a great range of non-speech motor phenomena, but as yet has not received attention in the speech motor control community. Here, we review some of the key characteristics of speech motor control and what they say about the role of the CNS in the process. We then discuss prior efforts to model the role of CNS in speech motor control, and argue that these models have inherent limitations – limitations that are overcome by an SFC model of speech motor control which we describe. We conclude by discussing a plausible neural substrate of our model.

Traditionally, psycholinguistic models and models of speech motor control have approached the word production process from different angles and have remained, to a large extent, separate from one another. Ultimately, however, the process entails the entire pathway from semantic processing to articulation: producing a word from meaning requires activating a concept, retrieving the word, selecting its segments, ordering those segments into the right sequence, and finally articulating them with the correct timing. This chapter reviews the neural basis of word production from the complementary perspectives of the psycholinguistic literature and the speech motor control literature.

The cortical computations underlying feedback control in vocal production

Effects of auditory masking upon the speech of stutterers.

Many voice disorders are the result of intricate neural and/or biomechanical impairments that are poorly understood. The limited knowledge of their etiological and pathophysiological mechanisms hampers effective clinical management. Behavioral studies have been used concurrently with computational models to better understand typical and pathological laryngeal motor control. Thus far, however, a unified computational framework that quantitatively integrates physiologically relevant models of phonation with the neural control of speech has not been developed. Here, we introduce LaDIVA, a novel neurocomputational model with physiologically based laryngeal motor control. We combined the DIVA model (an established neural network model of speech motor control) with the extended body-cover model (a physics-based vocal fold model). The resulting integrated model, LaDIVA, was validated by comparing its model simulations with behavioral responses to perturbations of auditory vocal fundamental frequency (fo) feedback in adults with typical speech. LaDIVA demonstrated capability to simulate different modes of laryngeal motor control, ranging from short-term (i.e., reflexive) and long-term (i.e., adaptive) auditory feedback paradigms, to generating prosodic contours in speech. Simulations showed that LaDIVA’s laryngeal motor control displays properties of motor equivalence, i.e., LaDIVA could robustly generate compensatory responses to reflexive vocal fo perturbations with varying initial laryngeal muscle activation levels leading to the same output. The model can also generate prosodic contours for studying laryngeal motor control in running speech. LaDIVA can expand the understanding of the physiology of human phonation to enable, for the first time, the investigation of causal effects of neural motor control in the fine structure of the vocal signal.

Nonword repetition and identification skills in Kannada speaking school-aged children who do and do not stutter

Purpose Developmental language disorder (DLD), an unexplained problem using and understanding spoken language, has been hypothesized to have an underlying auditory processing component. Auditory feedback plays a key role in speech motor control. The current study examined whether auditory feedback is used to regulate speech production in a similar way by children with DLD and their typically developing (TD) peers. Method Participants aged 6-11 years completed tasks measuring hearing, language, first formant (F1) discrimination thresholds, partial vowel space, and responses to altered auditory feedback with F1 perturbation. Results Children with DLD tended to compensate more than TD children for the positive F1 manipulation and compensated less than TD children in the negative shift condition. Conclusion Our findings suggest that children with DLD make atypical use of auditory feedback.

This paper presents an industrial point of view regarding dialog description languages for dialog applications on embedded devices. We present GDML, a dialog description language developed for embedding dialogs in speech control systems in cars. Furthermore we present the environment used for developing speech dialog applications with GDML. As GDML is already used in existent products for years, we have collected a lot of experiences with it. This enables us, since we also worked with VoiceXML finally to compare both approaches.

Auditory feedback is critical for the development and maintenance of speech in humans. In contrast, studies of nonhuman primate vocal production generally report that subjects show little reliance on auditory input. We examined the extent to which cotton-top tamarin (Saguinus oedipus) vocal production is sensitive to perturbation of auditory feedback by manipulating the predictability of presentation of a 1 s burst of white noise during the production of the species-specific contact call, the combination long call (CLC). We used three experimental conditions: the Begin condition, in which white noise was presented only during the first half of a recording session, the End condition, in which white noise was presented only in the last half, and the Random condition, in which each call had a 50% probability of receiving white noise playback throughout the recording session, making the auditory feedback unpredictable. In addition we recorded calls before and after the experimental series (Baseline condition) to determine whether any changes induced by modification of auditory feedback persisted. Results showed that playback of white noise during the production of the CLC produced changes in the temporal structure of the CLC: calls were shorter and had fewer pulses, indicating that modification of auditory feedback can interrupt vocal production. In addition, calls that received modified feedback were louder and had longer inter-pulse intervals than those that did not, consistent with an adaptive response to the masking effect of white noise playback. The magnitude of this compensatory effect and the interruption rate were both sensitive to whether the feedback modification occurred at the beginning or end of the experimental session: early feedback produced less interruption and more compensation. Finally, when auditory feedback modification was unpredictable, adaptive changes were observed in both calls that received modified feedback and those that received normal feedback, suggesting that tamarins can generate an expectation of noise playback and increase vocal amplitude in anticipation of masking.

Modulation of vocal pitch is a key speech feature that conveys important linguistic and affective information. Auditory feedback is used to monitor and maintain pitch. We examined induced neural high gamma power (HGP) (65-150 Hz) using magnetoencephalography during pitch feedback control. Participants phonated into a microphone while hearing their auditory feedback through headphones. During each phonation, a single real-time 400 ms pitch shift was applied to the auditory feedback. Participants compensated by rapidly changing their pitch to oppose the pitch shifts. This behavioral change required coordination of the neural speech motor control network, including integration of auditory and somatosensory feedback to initiate change in motor plans. We found increases in HGP across both hemispheres within 200 ms of pitch shifts, covering left sensory and right premotor, parietal, temporal, and frontal regions, involved in sensory detection and processing of the pitch shift. Later responses to pitch shifts (200-300 ms) were right dominant, in parietal, frontal, and temporal regions. Timing of activity in these regions indicates their role in coordinating motor change and detecting and processing of the sensory consequences of this change. Subtracting out cortical responses during passive listening to recordings of the phonations isolated HGP increases specific to speech production, highlighting right parietal and premotor cortex, and left posterior temporal cortex involvement in the motor response. Correlation of HGP with behavioral compensation demonstrated right frontal region involvement in modulating participant's compensatory response. This study highlights the bihemispheric sensorimotor cortical network involvement in auditory feedback-based control of vocal pitch.

The nervous system receives both auditory and somatosensory information as we talk. Little is known about the role of somatosensory input in speech motor control. It is indeed a longstanding puzzle how post-lingually deaf speakers, in the absence of any substantial auditory input, maintain speech intelligibility. In this study we have assessed the role of somatosensory feedback in subjects with cochlear implants who were tested with their implants turned off. We used a robotic device to alter speech movements, and hence somatosensory feedback, by delivering mechanical loads to the jaw. We found that with training subjects corrected for the loads, such that the motion path approached that normally experienced under no-load conditions. Thus even under no auditory feedback, somatosensory input mediates speech movements in post-lingually deaf adults. In this study all five subjects with cochlear implants showed varying degrees of adaptation compared to only four out of six subjects in an age matched control group. This suggests a prominent role for somatosensory feedback in individuals with hearing loss. Finally, movement kinematic patterns for subjects with hearing loss were no different than those of subjects with normal hearing, which further underscores the reliance on somatosensory feedback in deaf adults.

The role of proprioceptive and auditory feedback on speech motor control