Reverse Correlation Characterizes More Complete Tinnitus Spectra in Patients.

We validate a recent reverse correlation approach to tinnitus characterization by applying it to individuals with clinically-diagnosed tinnitus. Two tinnitus patients assessed the subjective similarity of their non-tonal tinnitus percepts and random auditory stimuli. Regression of the responses onto the stimuli yielded reconstructions which were evaluated qualitatively by playing back resynthesized waveforms to the subjects and quantitatively by response prediction analysis.

A compressive sensing approach for inferring cognitive representations with reverse correlation.

Uncovering cognitive representations is an elusive goal that is increasingly pursued using the reverse correlation method, wherein human subjects make judgments about ambiguous stimuli. Employing reverse correlation often entails collecting thousands of stimulus-response pairs, which severely limits the breadth of studies that are feasible using the method. Current techniques to improve efficiency bias the outcome.

Reverse Correlation Uncovers More Complete Tinnitus Spectra.

This study validates an approach to characterizing the sounds experienced by tinnitus patients via reverse correlation, with potential for characterizing a wider range of sounds than currently possible. Ten normal-hearing subjects assessed the subjective similarity of random auditory stimuli and target tinnitus-like sounds ("buzzing" and "roaring"). Reconstructions of the targets were obtained by regressing subject responses on the stimuli, and were compared for accuracy to the frequency spectra of the targets using Pearson's [Formula: see text].

Compliance With In-Home Self-Managed Rehabilitation Post-Stroke is Largely Independent of Scheduling Approach.

Objective: To investigate how participants self-schedule their engagement with domestic rehabilitation gaming platform, and how their scheduling behavior in turn influence overall compliance.

Design: Cohort of individuals randomized to receive in-home rehabilitation gaming during a multi-site randomized controlled trial.

Setting: In-home self-managed rehabilitation.

Dynamic Stability of Passive Dynamic Walking Following Unexpected Perturbations.

Mitigating the risk of falling is an area of significant interest among clinicians due to the often profound health-related consequences of falls. Consequently, there is acute interest in characterizing the biomechanical conditions associated with increased fall risk, and in methods for quantifying gait stability under those conditions toward predicting and ultimately preventing falls. Considerable insights into the biomechanics of fall risk have been provided by examining the passive dynamic walking (PDW) model under nominal and perturbed conditions.

The efficacy of acoustic-based articulatory phenotyping for characterizing and classifying four divergent neurodegenerative diseases using sequential motion rates.

Despite the impacts of neurodegeneration on speech function, little is known about how to comprehensively characterize the resulting speech abnormalities using a set of objective measures. Quantitative phenotyping of speech motor impairments may have important implications for identifying clinical syndromes and their underlying etiologies, monitoring disease progression over time, and improving treatment efficacy. The goal of this research was to investigate the validity and classification accuracy of comprehensive acoustic-based articulatory phenotypes in speakers with distinct neurodegenerative diseases.

Stimulus whitening improves the efficiency of reverse correlation.

Human perception depends upon internal representations of the environment that help to organize the raw information available from the senses by acting as reference patterns. Internal representations are widely characterized using reverse correlation, a method capable of producing unconstrained estimates of the representation itself, all on the basis of simple responses to random stimuli. Despite its advantages, reverse correlation is often infeasible to apply because of its inefficiency-a very large number of stimulus-response trials are required in order to obtain an accurate estimate.

Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment.

Smartphones can be used to passively assess and monitor patients' speech impairments caused by ailments such as Parkinson's disease, Traumatic Brain Injury (TBI), Post-Traumatic Stress Disorder (PTSD) and neurodegenerative diseases such as Alzheimer's disease and dementia. However, passive audio recordings in natural settings often capture the speech of non-target speakers (cross-talk). Consequently, speaker separation, which identifies the target speakers' speech in audio recordings with two or more speakers' voices, is a crucial pre-processing step in such scenarios.

Continuous TBI Monitoring From Spontaneous Speech Using Parametrized Sinc Filters and a Cascading GRU.

Traumatic Brain Injury (TBI) is caused by a head injury that affects the brain, impairing cognitive and communication function and resulting in speech and language disorders. Over 80,000 individuals in the US suffer from long-term TBI disabilities and continuous monitoring after TBI is essential to facilitate rehabilitation and prevent regression. Prior work has demonstrated the feasibility of TBI monitoring from speech by leveraging advancements in Artificial Intelligence (AI) and speech processing technology.

Validation of an Acoustic-Based Framework of Speech Motor Control: Assessing Criterion and Construct Validity Using Kinematic and Perceptual Measures.

Purpose: This study investigated the criterion (analytical and clinical) and construct (divergent) validity of a novel, acoustic-based framework composed of five key components of motor control: Coordination, Consistency, Speed, Precision, and Rate.

Method: Acoustic and kinematic analyses were performed on audio recordings from 22 subjects with amyotrophic lateral sclerosis during a sequential motion rate task. Perceptual analyses were completed by two licensed speech-language pathologists, who rated each subject's speech on the five framework components and their overall severity.

Dark tone quality and vocal tract shaping in soprano song production: Insights from real-time MRI.

Tone quality termed "dark" is an aesthetically important property of Western classical voice performance and has been associated with lowered formant frequencies, lowered larynx, and widened pharynx. The present study uses real-time magnetic resonance imaging with synchronous audio recordings to investigate dark tone quality in four professionally trained sopranos with enhanced ecological validity and a relatively complete view of the vocal tract. Findings differ from traditional accounts, indicating that labial narrowing may be the primary driver of dark tone quality across performers, while many other aspects of vocal tract shaping are shown to differ significantly in a performer-specific way.

Sensorimotor conflict tests in an immersive virtual environment reveal subclinical impairments in mild traumatic brain injury.

Current clinical tests lack the sensitivity needed for detecting subtle balance impairments associated with mild traumatic brain injury (mTBI). Patient-reported symptoms can be significant and have a huge impact on daily life, but impairments may remain undetected or poorly quantified using clinical measures. Our central hypothesis was that provocative sensorimotor perturbations, delivered in a highly instrumented, immersive virtual environment, would challenge sensory subsystems recruited for balance through conflicting multi-sensory evidence, and therefore reveal that not all subsystems are performing optimally.

Predicting changes in performance due to cognitive fatigue: A multimodal approach based on speech motor coordination and electrodermal activity.

Objective: Military job and training activities place significant demands on service members' (SMs') cognitive resources, increasing risk of injury and degrading performance. Early detection of cognitive fatigue is essential to reduce risk and support optimal function. This paper describes a multimodal approach, based on changes in measures of speech motor coordination and electrodermal activity (EDA), for predicting changes in performance following sustained cognitive effort.

Analysis of Phonetic Balance in Standard English Passages.

Purpose A common way of eliciting speech from individuals is by using passages of written language that are intended to be read aloud. Read passages afford the opportunity for increased control over the phonetic properties of elicited speech, of which phonetic balance is an often-noted example. No comprehensive analysis of the phonetic balance of read passages has been reported in the literature.

Bridging Dynamical Systems and Optimal Trajectory Approaches to Speech Motor Control With Dynamic Movement Primitives.

Current models of speech motor control rely on either trajectory-based control (DIVA, GEPPETO, ACT) or a dynamical systems approach based on feedback control (Task Dynamics, FACTS). While both approaches have provided insights into the speech motor system, it is difficult to connect these findings across models given the distinct theoretical and computational bases of the two approaches. We propose a new extension of the most widely used dynamical systems approach, Task Dynamics, that incorporates many of the strengths of trajectory-based approaches, providing a way to bridge the theoretical divide between what have been two separate approaches to understanding speech motor control.

Current models of speech motor control: A control-theoretic overview of architectures and properties.

This paper reviews the current state of several formal models of speech motor control, with particular focus on the low-level control of the speech articulators. Further development of speech motor control models may be aided by a comparison of model attributes. The review builds an understanding of existing models from first principles, before moving into a discussion of several models, showing how each is constructed out of the same basic domain-general ideas and components-e.

Speed-accuracy tradeoffs in human speech production.

Speech motor actions are performed quickly, while simultaneously maintaining a high degree of accuracy. Are speed and accuracy in conflict during speech production? Speed-accuracy tradeoffs have been shown in many domains of human motor action, but have not been directly examined in the domain of speech production. The present work seeks evidence for Fitts' law, a rigorous formulation of this fundamental tradeoff, in speech articulation kinematics by analyzing USC-TIMIT, a real-time magnetic resonance imaging data set of speech production.

On Short-Time Estimation of Vocal Tract Length from Formant Frequencies.

Vocal tract length is highly variable across speakers and determines many aspects of the acoustic speech signal, making it an essential parameter to consider for explaining behavioral variability. A method for accurate estimation of vocal tract length from formant frequencies would afford normalization of interspeaker variability and facilitate acoustic comparisons across speakers. A framework for considering estimation methods is developed from the basic principles of vocal tract acoustics, and an estimation method is proposed that follows naturally from this framework.

Co-registration of speech production datasets from electromagnetic articulography and real-time magnetic resonance imaging.

This paper describes a spatio-temporal registration approach for speech articulation data obtained from electromagnetic articulography (EMA) and real-time Magnetic Resonance Imaging (rtMRI). This is motivated by the potential for combining the complementary advantages of both types of data. The registration method is validated on EMA and rtMRI datasets obtained at different times, but using the same stimuli.