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Journal of Speech, Language, and... Jan 2022Despite extensive research into communication-related parameters in dysarthria, such as intelligibility, naturalness, and perceived listener effort, the existing...
PURPOSE
Despite extensive research into communication-related parameters in dysarthria, such as intelligibility, naturalness, and perceived listener effort, the existing evidence has not been translated into a clinically applicable, comprehensive, and valid diagnostic tool so far. This study addresses Communication-Related Parameters in Speech Disorders (KommPaS), a new web-based diagnostic instrument for measuring indices of communication limitation in individuals with dysarthria through online crowdsourcing. More specifically, it answers questions about the construct validity of KommPaS. In the first part, the interrelationship of the KommPaS variables were explored in order to draw a comprehensive picture of a patient's limitations and avoid the collection of redundant information. Second, the influences of motor speech symptoms on the KommPaS variables were studied in order to delineate the structural relationships between two complementary diagnostic perspectives.
METHOD
One hundred persons with dysarthria of different etiologies and varying degrees of severity were examined with KommPaS to obtain layperson-based data on communication-level parameters, and with the Bogenhausen Dysarthria Scale (BoDyS) to obtain expert-based, function-level data on dysarthria symptoms. The internal structure of the KommPaS variables and their dependence on the BoDyS variables were analyzed using structural equation modeling.
RESULTS
Despite a high multicollinearity, all KommPaS variables were shown to provide complementary diagnostic information and their mutual interconnections were delineated in a path graph model. Regarding the influence of the BoDyS scales on the KommPaS variables, separate linear regression models revealed plausible predictor sets. A complete path model of KommPaS and BoDyS variables was developed to map the complex interplay between variables at the functional and the communication levels of dysarthria assessment.
CONCLUSION
In validating a new clinical tool for the diagnostics of communication limitations in dysarthria, this study is the first to draw a comprehensive picture of how auditory-perceptual characteristics of dysarthria interact at the levels of expert-based functional and layperson-based communicative assessments.
Topics: Cognition; Dysarthria; Humans; Mobile Applications; Speech Intelligibility; Speech Production Measurement
PubMed: 34890213
DOI: 10.1044/2021_JSLHR-21-00215 -
Folia Phoniatrica Et Logopaedica :... 2022Evaluation of multiple domains, such as language, articulation, and cognitive function, is frequently required in neurological communicative disorders. The purpose of...
INTRODUCTION
Evaluation of multiple domains, such as language, articulation, and cognitive function, is frequently required in neurological communicative disorders. The purpose of this study was to investigate the performance of a 10-min screening scale for estimating aphasia, dysarthria, and cognitive dysfunction using a multicenter, large-sized consecutive series.
METHODS
We conducted a multicenter validation study that included 314 patients with brain injury between February 1 and June 31, 2018, from 20 medical centers across Japan. The Screening Test for Aphasia and Dysarthria (STAD) was developed in Japan in 2009, and a previous smaller-scale retrospective study established its high to moderate validity. All patients had undergone the STAD, and 212 of them underwent the Western Aphasia Battery or Assessment of Motor Speech for Dysarthria. The effect size on all 29 items and receiver operating curves of 3 sections of the STAD were analyzed based on external criteria, which were decided considering the clinical diagnosis of aphasia, dysarthria, and cognitive dysfunction. Correlations between the STAD and reference tests were calculated.
RESULTS
The phi coefficients of 23 out of 29 items exceeded the moderate effect size of 0.3 toward the targeted disorder. Overall, there was a good balance between sensitivity (82-92%) and specificity (77-78%), with moderate to large positive and negative likelihood ratios (3.7-4.19 and 0.1-0.23). The Pearson's r between the verbal section and Western Aphasia Battery Aphasia Quotient, the articulation section and Assessment of Motor Speech for Dysarthria, and the nonverbal section and Western Aphasia Battery Nonlinguistic Skills were 0.89, 0.70, and 0.79, respectively.
CONCLUSION
We demonstrated that the STAD has acceptable content and concurrent validity for the assessment of communicative function in patients with brain injury. This short screening tool can be useful in specific contexts, such as in early bedside investigations, to obtain a quick summary of communicative function prior to the administration of other tests, and in cases where more in-depth testing is not feasible.
Topics: Aphasia; Brain Injuries; Communication Disorders; Dysarthria; Humans; Japan; Retrospective Studies
PubMed: 34510047
DOI: 10.1159/000519381 -
Medicine May 2020To investigate the patterns of dysarthria in Korean patients with idiopathic peripheral facial palsy.Seventy-eight patients diagnosed with idiopathic peripheral facial...
To investigate the patterns of dysarthria in Korean patients with idiopathic peripheral facial palsy.Seventy-eight patients diagnosed with idiopathic peripheral facial palsy within the onset of symptom to 7 day time frame were prospectively enrolled. The initial symptom of facial palsy was examined by the House-Brackmann scale. All patients were tested by Urimal-Test of Articulation and Phonology-2 (U-TAP-2), which is specialized for the evaluation of dysarthria in Korean language - Hangeul - when the patients first visited and were followed up at 4 weeks after the onset, respectively. The facial electromyography was performed after 7 days, since the presentation of the first symptom. Electric stimulation therapy and simple facial exercise education were performed in all patients as routine treatments for facial palsy with or without dysarthria. The patterns of dysarthria were analyzed by initial and follow-up U-TAP-2 results, respectively.Among 78 patients, 50 patients (64.1%) had dysarthria in the first assessment. The 6 consonants and 3 vowels were errored in U-TAP-2 test. The bilabial consonants "ㅃ"[p] or "ㅍ" [p] were substituted with labiodental consonant [f], and palate-alveolar consonants were replaced by alveolar consonants - "ㅊ"[t(Equation is included in full-text article.)] to "ㅌ"[t]. Bilabial consonant "ㅁ"[m] was replaced by velar nasal consonant "ㅇ"[ŋ]. Liquid consonant was altered to nasal sound. For example, "ㄹ"[r] is replace by "ㄴ"[n]. The velar consonant "ㄲ"[k] was pronounced as "ㅋ" [k]. The diphthong vowels "ㅟ"[[Latin Small Letter Turned H]i], "ㅚ"[ø], or "ㅘ"[wa] were pronounced as monothong "ㅣ" [i], "ㅐ"[ε], or "ㅏ"[a], and "못"[mot] is slowly pronounced. After 4 weeks, 14 patients still showed pronunciation errors in 5 consonants and 3 vowels. The most common error was substitution.Among 78 patients with idiopathic peripheral facial palsy, 50 patients had dysarthria and 14 out of 50 patients with dysarthria lasted more than 4 weeks. Five consonants ("ㅁ", "ㅊ", "ㅍ", "ㄹ", "ㄲ") and 3 vowels ("ㅘ", "ㅗ", "ㅟ or ㅚ") were still mispronounced after 4 weeks, and most common error was substitution. Therefore, speech evaluation and speech therapy specialized for errors in high frequency of consonants and vowels are needed in patients with idiopathic peripheral facial palsy, in Korea.
Topics: Adult; Aged; Dysarthria; Facial Paralysis; Female; Humans; Language; Male; Middle Aged; Prospective Studies; Republic of Korea; Speech
PubMed: 32481249
DOI: 10.1097/MD.0000000000019585 -
Annual International Conference of the... Nov 2021In this paper, we propose a deep learning-based algorithm to improve the performance of automatic speech recognition (ASR) systems for aphasia, apraxia, and dysarthria...
In this paper, we propose a deep learning-based algorithm to improve the performance of automatic speech recognition (ASR) systems for aphasia, apraxia, and dysarthria speech by utilizing electroencephalography (EEG) features recorded synchronously with aphasia, apraxia, and dysarthria speech. We demonstrate a significant decoding performance improvement by more than 50% during test time for isolated speech recognition task and we also provide preliminary results indicating performance improvement for the more challenging continuous speech recognition task by utilizing EEG features. The results presented in this paper show the first step towards demonstrating the possibility of utilizing non-invasive neural signals to design a real-time robust speech prosthetic for stroke survivors recovering from aphasia, apraxia, and dysarthria. Our aphasia, apraxia, and dysarthria speech-EEG data set will be released to the public to help further advance this interesting and crucial research.
Topics: Aphasia; Apraxias; Brain; Dysarthria; Humans; Speech; Speech Perception
PubMed: 34892487
DOI: 10.1109/EMBC46164.2021.9629802 -
Journal of Medical Internet Research Oct 2022Most individuals with Parkinson disease (PD) experience a degradation in their speech intelligibility. Research on the use of automatic speech recognition (ASR) to...
BACKGROUND
Most individuals with Parkinson disease (PD) experience a degradation in their speech intelligibility. Research on the use of automatic speech recognition (ASR) to assess intelligibility is still sparse, especially when trying to replicate communication challenges in real-life conditions (ie, noisy backgrounds). Developing technologies to automatically measure intelligibility in noise can ultimately assist patients in self-managing their voice changes due to the disease.
OBJECTIVE
The goal of this study was to pilot-test and validate the use of a customized web-based app to assess speech intelligibility in noise in individuals with dysarthria associated with PD.
METHODS
In total, 20 individuals with dysarthria associated with PD and 20 healthy controls (HCs) recorded a set of sentences using their phones. The Google Cloud ASR API was used to automatically transcribe the speakers' sentences. An algorithm was created to embed speakers' sentences in +6-dB signal-to-noise multitalker babble. Results from ASR performance were compared to those from 30 listeners who orthographically transcribed the same set of sentences. Data were reduced into a single event, defined as a success if the artificial intelligence (AI) system transcribed a random speaker or sentence as well or better than the average of 3 randomly chosen human listeners. These data were further analyzed by logistic regression to assess whether AI success differed by speaker group (HCs or speakers with dysarthria) or was affected by sentence length. A discriminant analysis was conducted on the human listener data and AI transcriber data independently to compare the ability of each data set to discriminate between HCs and speakers with dysarthria.
RESULTS
The data analysis indicated a 0.8 probability (95% CI 0.65-0.91) that AI performance would be as good or better than the average human listener. AI transcriber success probability was not found to be dependent on speaker group. AI transcriber success was found to decrease with sentence length, losing an estimated 0.03 probability of transcribing as well as the average human listener for each word increase in sentence length. The AI transcriber data were found to offer the same discrimination of speakers into categories (HCs and speakers with dysarthria) as the human listener data.
CONCLUSIONS
ASR has the potential to assess intelligibility in noise in speakers with dysarthria associated with PD. Our results hold promise for the use of AI with this clinical population, although a full range of speech severity needs to be evaluated in future work, as well as the effect of different speaking tasks on ASR.
Topics: Humans; Dysarthria; Parkinson Disease; Artificial Intelligence; Speech Intelligibility; Speech Perception
PubMed: 36264608
DOI: 10.2196/40567 -
Journal of the Neurological Sciences Oct 2016Motor speech disorders are common in a number of neurological conditions including diseases involving impairment of the pyramidal, extrapyramidal, and cerebellar... (Review)
Review
Motor speech disorders are common in a number of neurological conditions including diseases involving impairment of the pyramidal, extrapyramidal, and cerebellar pathways, cranial nerves, muscular apparatus, neuromuscular plaque, and of cognitive, symbolic and mnestic activities. The diagnosis of speech disorders, namely the dysarthrias, involves the assessment of characteristic structural cerebral, prosodic, phonetic and phonemic changes, often flanked by concomitant functional, clinical, neuroradiological, neurophysiological and behavioral impairment. This paper presents a brief outline of the most significant associations to facilitate prompt differential diagnosis and thereby reduce the number of instrumental examinations required for diagnostic testing.
Topics: Apraxias; Diagnosis, Differential; Dysarthria; Humans; Speech; Verbal Behavior
PubMed: 27653923
DOI: 10.1016/j.jns.2016.08.048 -
Neurology Nov 2019Dysarthric speech of persons with Huntington disease (HD) is typically described as hyperkinetic; however, studies suggest that dysarthria can vary and resemble patterns...
OBJECTIVE
Dysarthric speech of persons with Huntington disease (HD) is typically described as hyperkinetic; however, studies suggest that dysarthria can vary and resemble patterns in other neurologic conditions. To test the hypothesis that distinct motor speech subgroups can be identified within a larger cohort of patients with HD, we performed a cluster analysis on speech perceptual characteristics of patient audio recordings.
METHODS
Audio recordings of 48 patients with mild to moderate dysarthria due to HD were presented to 6 trained raters. Raters provided scores for various speech features (e.g., voice, articulation, prosody) of audio recordings using the classic Mayo Clinic dysarthria rating scale. Scores were submitted to an unsupervised k-means cluster analysis to determine the most salient speech features of subgroups based on motor speech patterns.
RESULTS
Four unique subgroups emerged from the cohort of patients with HD. Subgroup 1 was characterized by an abnormally fast speaking rate among other unique speech features, whereas subgroups 2 and 3 were defined by an abnormally slow speaking rate. Salient speech features for subgroup 2 overlapped with subgroup 3; however, the severity of dysarthria differed. Subgroup 4 was characterized by mild deviations of speech features with typical speech rate. Length of CAG repeats, Unified Huntington's Disease Rating Scale total motor score, and percent intelligibility were significantly different for pairwise comparisons of subgroups.
CONCLUSION
This study supports the existence of distinct presentations of dysarthria in patients with HD, which may be due to divergent pathologic processes. The findings are discussed in relation to previous literature and clinical implications.
Topics: Adult; Aged; Cluster Analysis; Dysarthria; Female; Humans; Huntington Disease; Male; Middle Aged; Speech; Speech Acoustics
PubMed: 31662494
DOI: 10.1212/WNL.0000000000008541 -
Brain Injury Mar 2020: To review the current literature on interventions for dysarthria following traumatic brain injury (TBI) for their effectiveness and methodological quality, and... (Review)
Review
: To review the current literature on interventions for dysarthria following traumatic brain injury (TBI) for their effectiveness and methodological quality, and identify future directions for research in developing guidelines for treating dysarthria in this population.: Scoping review.: Electronic databases were searched up until July 2018 to find intervention trials for treating dysarthria following TBI. Articles were assessed by three reviewers to meet the following criteria: (1) population (adults with dysarthria following TBI only) and (2) intervention studies. Of the 1481 articles initially identified, 17 were selected based on inclusion criteria. 16 articles were single case designs (SCD) and one was a cohort study. Methodological qualities of eligible articles were examined using the single-case experimental design (SCED) rating scale; the cohort study was qualitatively described.: The interventions described fell into six broad categories - behavioral, prosthetic, instrumental, pharmacological, augmentative and alternative communication (AAC), and mixed intervention. Behavioral interventions received the most focus in the literature. The articles rated using the SCED received an average score of 6.8, indicating moderate methodological quality.: This field currently lacks high-quality research. Further research is required to determine the best clinical practice.
Topics: Adult; Behavior Therapy; Brain Injuries, Traumatic; Cohort Studies; Dysarthria; Humans
PubMed: 32064954
DOI: 10.1080/02699052.2020.1725844 -
Journal of Speech, Language, and... Mar 2022Oral diadochokinesis (DDK) is a standard dysarthria assessment task. To extract automatic and semi-automatic DDK measurements, numerous DDK analysis algorithms based on...
PURPOSE
Oral diadochokinesis (DDK) is a standard dysarthria assessment task. To extract automatic and semi-automatic DDK measurements, numerous DDK analysis algorithms based on acoustic signal processing are available, including amplitude based, spectral based, and hybrid. However, these algorithms have been predominantly validated in individuals with no perceptible to mild dysarthria. The behavior of these algorithms across dysarthria severity is largely unknown. Likewise, these algorithms have not been tested equally for various syllable types. The goal of this study was to evaluate the performance of five common DDK algorithms as a function of dysarthria severity, considering syllable types.
METHOD
We analyzed 282 DDK recordings of /ba/, /pa/, and /ta/ from 145 participants with amyotrophic lateral sclerosis. Recordings were stratified into mild, moderate, or severe dysarthria groups based on individual performance on the Speech Intelligibility Test. Analysis included manual and automatic estimation of the number of syllables, DDK rate, and cycle-to-cycle temporal variability (cTV). Validation metrics included Bland-Altman mixed-effects limits of agreement between manual and automatic syllable counts, recall and precision between manual and automatic syllable boundary detection, and Kendall's tau-b correlations between manual and algorithm-detected DDK rate and cTV.
RESULTS
The amplitude-based algorithm (absolute energy) yielded the strongest correlations with manual analysis across all severity groups for DDK rate ( = 0.7-0.84) and cTV ( = 0.7-0.84) and the narrowest limits of agreement (-5.92 to 7.12 syllable difference). Moreover, this algorithm also provided the highest mean recall and precision across severity groups for /ba/ and /pa/, but with significantly more variation for/ta/.
CONCLUSIONS
Algorithms based on signal energy analysis appeared to be the most robust for DDK analysis across dysarthria severity and syllable types; however, it remains prone to error against severe dysarthria and alveolar syllable context. Further development is needed to address this important issue.
Topics: Acoustics; Algorithms; Amyotrophic Lateral Sclerosis; Dysarthria; Humans; Speech Production Measurement
PubMed: 35171700
DOI: 10.1044/2021_JSLHR-21-00503 -
Clinical Rehabilitation Jun 2024To identify and agree on what outcome domains should be measured in research and clinical practice when working with stroke survivors who have dysarthria.
OBJECTIVE
To identify and agree on what outcome domains should be measured in research and clinical practice when working with stroke survivors who have dysarthria.
DESIGN
Delphi process, two rounds of an online survey followed by two online consensus meetings.
SETTING
UK and Australia.
PARTICIPANTS
Stroke survivors with experience of dysarthria, speech and language therapists/pathologists working in stroke and communication researchers.
METHODS
Initial list of outcome domains generated from existing literature and with our patient and public involvement group to develop the survey. Participants completed two rounds of this survey to rate importance. Outcomes were identified as 'in', 'unclear' or 'out' from the second survey. All participants were invited to two consensus meetings to discuss these results followed by voting to identify critically important outcome domains for a future Core Outcome Set. All outcomes were voted on in the consensus meetings and included if 70% of meeting participants voted 'yes' for critically important.
RESULTS
In total, 148 surveys were fully completed, and 28 participants attended the consensus meetings. A core outcome set for dysarthria after stroke should include four outcome domains: (a) intelligibility of speech, (b) ability to participate in conversations, (c) living well with dysarthria, (d) skills and knowledge of communication partners (where relevant).
CONCLUSIONS
We describe the consensus of 'what' speech outcomes after stroke are valued by all stakeholders including those with lived experience. We share these findings to encourage the measurement of these domains in clinical practice and research and for future research to identify 'how' best to measure these outcomes.
Topics: Humans; Dysarthria; Delphi Technique; Stroke; Stroke Rehabilitation; Female; Male; Outcome Assessment, Health Care; Middle Aged; Australia; Consensus; Aged; Surveys and Questionnaires; United Kingdom
PubMed: 38374687
DOI: 10.1177/02692155241231929