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Introduction: Smart devices are widely available and capable of quickly recording and uploading speech segments for health-related analysis. The switch from laboratory recordings with professional-grade microphone setups to remote, smart device-based recordings offers immense potential for the scalability of voice assessment. Yet, a growing body of literature points to a wide heterogeneity among acoustic metrics for their robustness to variation in recording devices. The addition of consumer-grade plug-and-play microphones has been proposed as a possible solution. The aim of our study was to assess if the addition of consumer-grade plug-and-play microphones increases the acoustic measurement agreement between ultra-portable devices and a reference microphone. Methods: Speech was simultaneously recorded by a reference high-quality microphone commonly used in research and by two configurations with plug-and-play microphones. Twelve speech-acoustic features were calculated using recordings from each microphone to determine the agreement intervals in measurements between microphones. Agreement intervals were then compared to expected deviations in speech in various neurological conditions. Each microphone’s response to speech and to silence was characterized through acoustic analysis to explore possible reasons for differences in acoustic measurements between microphones. The statistical differentiation of two groups, neurotypical and people with multiple sclerosis, using metrics from each tested microphone was compared to that of the reference microphone. Results: The two consumer-grade plug-and-play microphones favored high frequencies (mean center of gravity difference ≥ +175.3 Hz) and recorded more noise (mean difference in signal to noise ≤ −4.2 dB) when compared to the reference microphone. Between consumer-grade microphones, differences in relative noise were closely related to distance between the microphone and the speaker’s mouth. Agreement intervals between t

Neurodegenerative disease often affects speech. Speech acoustics can be used as objective clinical markers of pathology. Previous investigations of pathological speech have primarily compared controls with one specific condition and excluded comorbidities. We broaden the utility of speech markers by examining how multiple acoustic features can delineate diseases. We used supervised machine learning with gradient boosting (CatBoost) to delineate healthy speech from speech of people with multiple sclerosis or Friedreich ataxia. Participants performed a diadochokinetic task where they repeated alternating syllables. We subjected 74 spectral and temporal prosodic features from the speech recordings to machine learning. Results showed that Friedreich ataxia, multiple sclerosis and healthy controls were all identified with high accuracy (over 82%). Twenty-one acoustic features were strong markers of neurodegenerative diseases, falling under the categories of spectral qualia, spectral power, and speech rate. We demonstrated that speech markers can delineate neurodegenerative diseases and distinguish healthy speech from pathological speech with high accuracy. Findings emphasize the importance of examining speech outcomes when assessing indicators of neurodegenerative disease. We propose large-scale initiatives to broaden the scope for differentiating other neurological diseases and affective disorders.

Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.

BACKGROUND: Multiple Sclerosis (MS) pathology is likely to disrupt central auditory pathways, thereby affecting an individual's ability to discriminate speech from noise. Despite the importance of speech discrimination in daily communication, it's characterization in the context of MS remains limited. This cross-sectional study evaluated speech discrimination in MS under "real world" conditions where sentences were presented in ecologically valid multi-talker speech or broadband noise at several signal-to-noise ratios (SNRs). METHODS: Pre-recorded Bamford-Kowal-Bench sentences were presented at five signal-to-noise ratios (SNR) in one of two background noises: speech-weighted noise and eight-talker babble. All auditory stimuli were presented via headphones to control (n = 38) and MS listeners with mild (n = 20), moderate (n = 16) and advanced (n = 10) disability. Disability was quantified by the Kurtzke Expanded Disability Status Scale (EDSS) and scored by a neurologist. All participants passed a routine audiometric examination. RESULTS: Despite normal hearing, MS psychometric discrimination curves which model the relationship between signal-to-noise ratio (SNR) and sentence discrimination accuracy in speech-weighted noise and babble did not change in slope (sentences/dB) but shifted to higher SNRs (dB) compared to controls. The magnitude of the shift in the curve systematically increased with greater disability. Furthermore, mixed-effects models identified EDSS score as the most significant predictor of speech discrimination in noise (odds ratio = 0.81; p < 0.001). Neither age, sex, disease phenotype or disease duration were significantly associated with speech discrimination performance in noise. Only MS listeners with advanced disability self-reported audio-attentional difficulty in a questionnaire designed to reflect auditory processing behaviours in daily life. CONCLUSION: Speech discrimination performance worsened systematically with greater disability, indepe

Automatic speech recognition (ASR) could potentially improve communication by providing transcriptions of speech in real time. ASR is particularly useful for people with progressive disorders that lead to reduced speech intelligibility or difficulties performing motor tasks. ASR services are usually trained on healthy speech and may not be optimized for impaired speech, creating a barrier for accessing augmented assistance devices. We tested the performance of three state-of-the-art ASR platforms on two groups of people with neurodegenerative disease and healthy controls. We further examined individual differences that may explain errors in ASR services within groups, such as age and sex. Speakers were recorded while reading a standard text. Speech was elicited from individuals with multiple sclerosis, Friedreich’s ataxia, and healthy controls. Recordings were manually transcribed and compared to ASR transcriptions using Amazon Web Services, Google Cloud, and IBM Watson. Accuracy was measured as the proportion of words that were correctly classified. ASR accuracy was higher for controls than clinical groups, and higher for multiple sclerosis compared to Friedreich’s ataxia for all ASR services. Amazon Web Services and Google Cloud yielded higher accuracy than IBM Watson. ASR accuracy decreased with increased disease duration. Age and sex did not significantly affect ASR accuracy. ASR faces challenges for people with neuromuscular disorders. Until improvements are made in recognizing less intelligible speech, the true value of ASR for people requiring augmented assistance devices and alternative communication remains unrealized. We suggest potential methods to improve ASR for those with impaired speech.

BACKGROUND AND PURPOSE: Objective measurement of speech has shown promising results to monitor disease state in multiple sclerosis. In this study, we characterize the relationship between disease severity and speech metrics through perceptual (listener based) and objective acoustic analysis. We further look at deviations of acoustic metrics in people with no perceivable dysarthria. METHODS: Correlations and regression were calculated between speech measurements and disability scores, brain volume, lesion load and quality of life. Speech measurements were further compared between three subgroups of increasing overall neurological disability: mild (as rated by the Expanded Disability Status Scale ≤2.5), moderate (≥3 and ≤5.5) and severe (≥6). RESULTS: Clinical speech impairment occurred majorly in people with severe disability. An experimental acoustic composite score differentiated mild from moderate (P < 0.001) and moderate from severe subgroups (P = 0.003), and correlated with overall neurological disability (r = 0.6, P < 0.001), quality of life (r = 0.5, P < 0.001), white matter volume (r = 0.3, P = 0.007) and lesion load (r = 0.3, P = 0.008). Acoustic metrics also correlated with disability scores in people with no perceivable dysarthria. CONCLUSIONS: Acoustic analysis offers a valuable insight into the development of speech impairment in multiple sclerosis. These results highlight the potential of automated analysis of speech to assist in monitoring disease progression and treatment response.

Objective: To objectively describe cerebellar mediated speech function using a multiparameter index that reflects pathology and quality of life in MS. Background: Cerebellar function plays a role in cognitive processing and motor control and is important for speech production. Multiple sclerosis (MS) can result in impaired cerebellar function, leading to speech deficits. These deficits can be detected by instrumental measurement. Speech as a marker of cerebellar impairment but is not well described. Method: The speech and clinical features of 85 people with MS (plus 21 matched controls) were assessed using objective acoustic analysis, validated questionnaires of quality of life and disease severity using the Scale for the Assessment and rating of Ataxia. Magnetic resonance imaging was used to measure cerebellar pathology. A regression model with eight speech variables were used to predict cerebellar function. A composite speech score was developed from the model and tested for prediction of fine motor function using the 9-hole peg test (9HPT), for correlations with imaging outcomes and self-assessed quality of life. Results: Speech timing metrics (eg. slow rate of syllable repetition, increased proportion of silence) were the strongest predictors of cerebellar impairment, alongside phonatory instability. The acoustic composite score accounted for 54% of variation in cerebellar dysfunction, was associated with cerebellar white matter volume (r=0.3, p=0.017), quality of life (r=0.5, p<0.001) and predicted an abnormal 9HPT with 85% accuracy. Conclusion: Motor cerebellar impairment in MS was reflected in an objective multi-feature speech metric.

The most complex interactions between human beings occur through speech, and often in the presence of background noise. Understanding speech in noisy environments requires the integrity of highly integrated and widespread auditory networks likely to be impacted by multiple sclerosis (MS) related neurogenic injury. Despite the impact auditory communication has on a person's ability to navigate the world, build relationships, and maintain employability; studies of speech-in-noise (SiN) perception in people with MS (pwMS) have been minimal to date. Thus, this paper presents a dataset related to the acquisition of pure-tone thresholds, SiN performance and questionnaire responses in age-matched controls and pwMS. Bilateral pure-tone hearing thresholds were obtained at frequencies of 250 hertz (Hz), 500 Hz, 750 Hz, 1000 Hz, 1500 Hz, 2000 Hz, 4000 Hz, 6000 Hz and 8000 Hz, and hearing thresholds were defined as the lowest level at which the tone was perceived 50% of the time. Thresholds at 500 Hz, 1000 Hz, 2000 Hz and 4000 Hz were used to calculate the four-tone average for each participant, and only those with a bilateral four tone average of ≤ 25 dB HL were included in the analysis. To investigate SiN performance in pwMS, pre-recorded Bamford-Kowal-Bench (BKB) sentences were presented binaurally through headphones at five signal-to-noise ratios (SNR) in two noise conditions: speech-weighted noise and multi-talker babble. Participants were required to verbally repeat each sentence they had just heard; or indicate their inability to do so. A 33-item questionnaire, based on validated inventories for specific adult clinical populations with abnormal auditory processing, was used to evaluate auditory processing in daily life for pwMS. For analysis, pwMS were grouped according to their Expanded Disability Status Scale (EDSS) score as rated by a neurologist. PwMS with EDSS scores ≤ 1.5 were classified as 'mild' (n = 20); between 2 and 4.5 as 'moderate' (n = 16) and between 5 and

Wearing face masks (alongside physical distancing) provides some protection against infection from COVID-19. Face masks can also change how people communicate and subsequently affect speech signal quality. This study investigated how three common face mask types (N95, surgical, and cloth) affected acoustic analysis of speech and perceived intelligibility in healthy subjects. Acoustic measures of timing, frequency, perturbation, and power spectral density were measured. Speech intelligibility and word and sentence accuracy were also examined using the Assessment of Intelligibility of Dysarthric Speech. Mask type impacted the power distribution in frequencies above 3 kHz for the N95 mask, and above 5 kHz in surgical and cloth masks. Measures of timing and spectral tilt mainly differed with N95 mask use. Cepstral and harmonics to noise ratios remained unchanged across mask type. No differences were observed across conditions for word or sentence intelligibility measures; however, accuracy of word and sentence translations were affected by all masks. Data presented in this study show that face masks change the speech signal, but some specific acoustic features remain largely unaffected (e.g., measures of voice quality) irrespective of mask type. Outcomes have bearing on how future speech studies are run when personal protective equipment is worn.

ABSTRACT

Background: Parkinson’s disease (PD) frequently causes progressive deterioration in speech, voice and cognitive aspects of communication. These affect wellbeing and quality of life and are associated with caregiver strain and burden. Therapeutic singing groups can ameliorate PD-related communication disorders and increase social interaction and wellbeing for caregivers and care recipients. Objective: To analyse the effects of ParkinSong group singing sessions on Parkinson’s communication and wellbeing outcomes for people with PD and caregivers over 12 months. Methods: A 4-armed controlled clinical trial compared ParkinSong with active non-singing control conditions over 12 months. Two dosage levels (weekly versus monthly) were available for each condition. ParkinSong comprised high-effort vocal, respiratory and speech exercises, group singing, and social interaction. PD-specific outcomes included vocal loudness, speech intelligibility, maximum phonation time, respiratory muscle strength, and voice related quality of life (QoL). Wellbeing outcomes were also measured for caregivers and care recipients. Results: We recruited 75 people with PD and 44 caregivers who attended weekly ParkinSong, monthly ParkinSong, weekly control or monthly control groups. We found significant improvements in the primary outcome of vocal loudness (p = 0.032), with weekly singers 5.13 dB louder (p = 0.044) and monthly singers 5.69 dB louder (p = 0.015) than monthly controls at 12 months. ParkinSong participants also showed greater improvements in voice-related QoL and anxiety. Caregivers who attended ParkinSong showed greater reductions in depression and stress scores. Conclusions: This 12-month controlled clinical trial of ParkinSong demonstrated improvements in speech loudness and voice-related QoL for participants with PD, and enhanced wellbeing for both caregivers and care recipients. No adverse effects were reported over 12 months and improvements were sustained.

BACKGROUND: Tremor is a debilitating symptom of Multiple Sclerosis (MS). Little is known about its pathophysiology and treatments are limited. Clinical trials investigating new interventions often rely on subjective clinical rating scales to provide supporting evidence of efficacy. NEW METHOD: We present a novel instrument (TREMBAL) which uses electromagnetic motion capture technology to quantify MS tremor. We aim to validate TREMBAL by comparison to clinical ratings using regression modelling with 310 samples of tremor captured from 13 MS participants who performed five different hand exercises during several follow-up visits. Minimum detectable change (MDC) and test-retest reliability were calculated and comparisons were made between MS tremor and data from 12 healthy volunteers. RESULTS: Velocity of the index finger was most congruent with clinical observation. Regression modelling combining different features, sensor configurations, and labelling exercises did not improve results. TREMBAL MDC was 84% of its initial measurement compared to 91% for the clinical rating. Intra-class correlations for test-retest reliability were 0.781 for TREMBAL and 0.703 for clinical ratings. Tremor was lower (p = 0.002) in healthy subjects. COMPARISON WITH EXISTING METHODS: Subjective scales have low sensitivity, suffer from ceiling effects, and mitigation against inter-rater variability is challenging. Inertial sensors are ubiquitous, however, their output is nonlinearly related to tremor frequency, compensation is required for gravitational artefacts, and their raw data cannot be intuitively comprehended. CONCLUSIONS: TREMBAL, compared with clinical ratings, gave measures in agreement with clinical observation, had marginally lower MDC, and similar test-retest reliability.

Introduction: Tremor of the upper limbs is a disabling symptom that is present during several neurological disorders and is currently without treatment. Functional MRI (fMRI) is an essential tool to investigate the pathophysiology of tremor and aid the development of treatment options. However, no adequately or standardized protocols for fMRI exists at present. Here we present a novel, online available fMRI task that could be used to assess the in vivo pathology of tremor. Objective: This study aims to validate the tremor-evoking potential of the fMRI task in a small group of tremor patients outside the scanner and assess the reproducibility of the fMRI task related activation in healthy controls. Methods: Twelve HCs were scanned at two time points (baseline and after 6-weeks). There were two runs of multi-band fMRI and the tasks included a "brick-breaker" joystick game. The game consisted of three conditions designed to control for most of the activation related to performing the task by contrasting the conditions: WATCH (look at the game without moving joystick), MOVE (rhythmic left/right movement of joystick without game), and PLAY (playing the game). Task fMRI was analyzed using FSL FEAT to determine clusters of activation during the different conditions. Maximum activation within the clusters was used to assess the ability to control for task related activation and reproducibility. Four tremor patients have been included to test ecological and construct validity of the joystick task by assessing tremor frequencies captured by the joystick. Results: In HCs the game activated areas corresponding to motor, attention and visual areas. Most areas of activation by our game showed moderate to good reproducibility (intraclass correlation coefficient (ICC) 0.531-0.906) with only inferior parietal lobe activation showing poor reproducibility (ICC 0.446). Furthermore, the joystick captured significantly more tremulous movement in tremor patients compared to HCs (p = 0.01)

IMPORTANCE: Multiple sclerosis produces neurological impairments that are variable in duration, severity and quality. Speech is frequently impaired, resulting in decreased communication skills and quality of life. Advancements in technology now makes it possible to use quantitative acoustic assessment of speech as biomarkers of disease progression. OBSERVATIONS: Four domains of speech have been identified: articulation (slow articulation and imprecise consonants), voice (pitch and loudness instability), respiration (decreased phonatory time and expiratory pressure) and prosody (longer and frequent pauses, deficient loudness control). Studies also explored I) predictive models for diagnosis of MS and of ataxia using speech variables, II) the relationship of dysarthria with cognition and III) very few studies correlated neuroimaging with dysarthria. We could not identify longitudinal studies of speech or dysarthria in Multiple Sclerosis. CONCLUSION AND RELEVANCE: Refinement of objective measures of speech has enhanced our understanding of Multiple Sclerosis-related deficits in cross-sectional analysis while both integrative and longitudinal studies are identified as major gaps. This review highlights the potential for using quantitative acoustic assessments as clinical endpoints for diagnosing, monitoring progression and treatment in disease modifying trials.

Background: Dysarthria is highly prevalent in Multiple Sclerosis. The relationship between dysarthria, MS disease severity and other cerebellar manifestations (such as tremor) is poorly understood. Objective: To examine the relationship between objective markers of speech, disease severity and upper limb tremor in relapsing-remitting and secondary progressive Multiple Sclerosis. Design Methods: An experienced neurologist determined A) the presence of upper limb tremor, B) the Expanded Disability Status Scale (EDSS) score and C) the degree of dysarthria (from 0, no disturbance to 4, unintelligible). Through acoustic analysis of speech, we investigated: 1) stability of vocal pitch, in sustained utterance of the vowel /a/; 2) stability of loudness, in the same sustained vowel; 3) diadochokinetic speed, in fast repetition of the meaningless word /pa/ta/ka/ and 4) maximum speed of vocal tract movement (i.e. change in pharynx and mouth cavity shape), measured in the word “always” (from a standard reading passage). After adjustment for multiple comparisons, p<0.0125 was considered for statistical significance. Results: We assessed 24 participants with Multiple Sclerosis and upper limb tremor (47.2±12.3years, 75% female, EDSS=3.7±1.6) and 24 matched patients with Multiple Sclerosis without tremor (51.2±10.7years, 75% female, EDSS=3.6±1.7). Clinical dysarthria scores (median=0, mean=0.375±0.76) correlated with all acoustic variables measured: diadochokinetic speed Spearman’s rho=.561 (p<.001); pitch stability rho=.37 (p=.011); loudness stability rho=.37 (p=.01); and maximum speed of vocal tract movement rho=.363 (p=.012). Diadochokinetic speed strongly correlated with EDSS (rho=.529, p<.001). Speed of vocal tract movement correlated with tremor and differentiated tremor and non-tremor groups (2-tailed t-test p=0.002, rho=.418). Conclusions: In a typically non-to-mildly dysarthric cohort, acoustic speech measurements correlate with disease severity and can differentiate overt

Background: Reduction of brain volume occurs in clinically active disease and correlates with progressive disability in multiple Sclerosis (MS). Although dysarthria is highly prevalent in MS, it only becomes clinically relevant in advanced stages of the disease. The relationship between early sub-clinical markers of dysarthria and overall disease severity is poorly understood. Aim: To examine the relationship between an objective marker of speech performance and validated clinical scores for disease severity in non-dysarthric subjects with relapsing-remitting and secondary progressive MS. Method: An experienced neurologist scored patients according to the Expanded Disability Status Scale (EDSS) and the Scale for the Assessment and Rating of Ataxia (SARA). Acoustic analysis was used to investigate the diadochokinetic speed in “as fast as possible” repetition of the meaningless word /pa/ta/ka/. Brain images were acquired using 3 Tesla magnetic resonance. Images were automatically segmented using FreeSurfer (5.7) to determine volumes for whole brain (excluding ventricules) and cerebellum. Lesions were automatically segmented by the lesion prediction algorithm as implemented in the Lesion Segmentation Tool version 2.0.15 for SPM (Statistical Parametric Mapping software). Statistical correlations were processed in SPSS (v 23.0) controlling for age. After adjustment for multiple comparisons, a p< 0.01 was considered for statistical significance. Results: We assessed 35 MS patients with normal speech (i.e. SARA speech sub-score 0-1; age=47.7±12years; disease duration=13.2±8.4). Diadochokinetic rate (mean=5.63±0.83 syllables per second) directly correlated with EDSS (Spearman's rho=0.454, 2-tailed p=0.007; median EDSS=3.5, interquartile range=3.5) and SARA (rho=0.515, p=0.002; SARA median=9, interquartile range 11.975), but not with whole brain volume (p=0.022), lesion load (p=0.032) or cerebellar volume (p=0.037). Conclusion: Changes in acoustic markers can be detected bef

Background: Dysarthria is highly prevalent in Multiple Sclerosis (MS). The relationship between dysarthria, MS disease severity and other cerebellar manifestations (such as tremor) is poorly understood. Aim: To examine the relationship between objective markers of speech, disease severity and upper limb tremor in relapsing-remitting and secondary progressive MS. Method: An experienced neurologist determined A) the presence of upper limb tremor, B) the Expanded Disability Status Scale (EDSS) score and C) the degree of dysarthria (from 0, no disturbance to 4, unintelligible). We used acoustic analysis to investigate 4 speech domains: 1) stability of vocal pitch, in sustained utterance of the vowel /a/; 2) stability of loudness, in the same sustained vowel; 3) diadochokinetic speed, in fast repetition of the meaningless word /pa/ta/ka/ and 4) maximum speed of vocal tract movement (i.e. change in pharynx and mouth cavity shape), measured through change in the second formant frequency in the word “always”, from reading of the “Grandfather Passage”. After adjustment for multiple comparisons, a p< 0.0125 was considered for statistical significance. Results: We assessed 24 MS patients with upper limb tremor (47.2±12.3years, 75% female, EDSS=3.7±1.6) and 24 matched patients without tremor (51.2±10.7years, 75% female, EDSS=3.6±1.7). Clinical dysarthria (median=0, mean=0.375±0.76) moderately correlated with EDSS scores (Spearman's rho =.586, p< .001) and with syllable repetition rates (/pa/ta/ka/ rho=.561, p< .001), marginally correlated with speed of tract movement (rho=.363, p=.012), pitch stability (rho=.37, p=.011), loudness stability (rho=.37, p=.01) but not with upper limb tremor presence (p=.039). Only /pa/ta/ka/ rate correlated with EDSS (rho=.529, p< .001) and speed of tract movement differentiated tremor and non-tremor groups (2-tailed t-test p=0.002, rho=.418). Conclusion: Acoustic speech measurements correlate with MS disease severity and can differentiate overt ce

Type: Poster Abstract Category: Clinical aspects of MS - Clinical assessment tools Background: Tremor in MS (MST) is difficult to treat and the development of new interventions is limited by the absence of universal measuring systems. At present, therapeutic outcomes are measured by a variety of clinical rating scales that are subjective and lack sufficient sensitivity. With increasing use of interventional treatments such as Botulinum toxin injections or Deep Brain Stimulation for MST, it has become critical to develop precise measurement instruments. Objective: To clinically validate the TREMBAL software in MST. Methods: TREMBAL (Bionics Institute, Melbourne, Australia) utilises an electromagnetic motion tracker (Ascension, Vermont, US) to acquire absolute displacements and rotations of a tremulous body part. Tremor was recorded bilaterally from four locations (second phalanx of the middle finger, wrist dorsum, forearm and upper arm) in five positions (hands resting on lap, arms outstretched in front, finger-nose, batwing static and batwing action). Tremor exercises were video recorded (GoPro Hero3, GoPro Inc., San Mateo, California) and rated by two experts using the 5-point Unified Tremor Rating Assessment (UTRA) scale where 0=no tremor and 4=severe. TREMBAL tremor displacements (measured in units of millimetres) were averaged and log transformed to match the distribution of clinical ratings. Data were pooled across exercises. Congruence between TREMBAL measures and mean clinical ratings was explored using regression analysis and Pearson´s correlation. Results: We assessed ten MST patients over 6 months and rated 200 videos. The median pooled UTRA score was 0.5 (interquartile range 0, 1.5). The average TREMBAL recorded tremor displacement was 1.65 mm (standard deviation 2.1). A strong correlation between UTRA scores and log transformed TREMBAL displacement was found, r = 0.749, p< 0.001. Conclusions: TREMBAL measurements are highly accurate when compared to clin