“You Say Severe, I Say Mild”: Toward an Empirical Classification of Dysarthria Severity

Purpose: The main purpose of this study was to create an empirical classification system for speech severity in patients with dysarthria secondary to amyotrophic lateral sclerosis (ALS) by exploring the reliability and validity of speech-language pathologists' (SLPs') ratings of dysarthric speech. Method: Ten SLPs listened to speech samples from 52 speakers with ALS and 20 healthy control speakers. SLPs were asked to rate the speech severity of the speakers using five response options: normal, mild, moderate, severe, and profound. Four severity-surrogate measures were also calculated: SLPs transcribed the speech samples for the calculation of speech intelligibility and rated the effort it took to understand the speakers on a visual analog scale. In addition, speaking rate and intelligible speaking rate were calculated for each speaker. Intrarater and interrater reliability were calculated for each measure. We explored the validity of clinician-based severity ratings by comparing them to the severity-surrogate measures. Receiver operating characteristic (ROC) curves were conducted to create optimal cutoff points for defining dysarthria severity categories. Results: Intrarater and interrater reliability for the clinician-based severity ratings were excellent and were comparable to reliability for the severity-surrogate measures explored. Clinician severity ratings were strongly associated with all severity-surrogate measures, suggesting strong construct validity. We also provided a range of values for each severity-surrogate measure within each severity category based on the cutoff points obtained from the ROC analyses. Conclusions: Clinician severity ratings of dysarthric speech are reliable and valid. We discuss the underlying challenges that arise when selecting a stratification measure and offer recommendations for a classification scheme when stratifying patients and research participants into speech severity categories.

The situation of English speaker’s place of origin depending on Chinese dialects

This study examines the ability to identify different Chinese dialects through the English language and evaluates how often respondents pay attention to phonological features and rate of speech to explain their categorizations. The research includes 100 Chinese undergraduate students and 100 young people without advanced degrees aged 20 to 25. Discrete independent data samples collected during the interview of participants are analyzed with the help of such statistical methods as Student's t-test, Mann-Whitney U-test, and Wilcoxon's test. The obtained results indirectly show the ability of respondents to identify native and non-native English speakers around the world, as well as determine their nationality. The outcomes of the paper explicate who, in general, categorize Chinese dialects better and which dialects are the most recognizable. Research data reveal a high degree of stereotypization of various dialects, especially the Beijing and U dialects. Moreover, based on the data obtained, it can be concluded that speaking rate significantly affects the perception and classification of a speaker from a particular province of China.

Psychometric Properties of Rapid Word-Based Rate Measures in the Assessment of Bulbar Amyotrophic Lateral Sclerosis: Comparisons With Syllable-Based Rate Tasks

Purpose Rapid maximum performance repetition tasks have increasingly demonstrated their utility as clinimetric markers supporting diagnosis and monitoring of bulbar disease in amyotrophic lateral sclerosis (ALS). A recently developed protocol uses novel real-word repetitions instead of traditional nonword/syllable sequences in hopes of improving sensitivity to motor speech impairments by adding a phonological target constraint that would activate a greater expanse of the motor speech neuroanatomy. This study established the psychometric properties of this novel clinimetric protocol in its assessment of bulbar ALS and compared performance to traditional syllable sequence dysdiadochokinetic (DDK) tasks. Specific objectives were to (a) compare rates between controls and speakers with symptomatic versus presymptomatic bulbar disease, (b) characterize their discriminatory ability in detecting presymptomatic bulbar disease compared to healthy speech, (c) determine their articulatory movement underpinnings, and (d) establish within-individual longitudinal changes. Method DDK and novel tongue (“ticker”—TAR) and labial (“pepper”—LAR) articulatory rates were compared between n = 18 speakers with presymptomatic bulbar disease, n = 10 speakers with symptomatic bulbar disease, and n = 13 healthy controls. Bulbar disease groups were determined by a previously validated speaking rate cutoff. Discriminatory ability was determined using receiver operating characteristic analysis. Within-individual change over time was characterized in a subset of 16 participants with available longitudinal data using linear mixed-effects models. Real-time articulatory movements of the tongue front, tongue dorsum, jaw, and lips were captured using 3-D electromagnetic articulography; effects of movement displacement and speed on clinimetric rates were determined using stepwise linear regressions. Results All clinimetric rates (traditional DDK tasks and novel tasks) were reduced in speakers with symptomatic bulbar disease; only TAR was reduced in speakers with presymptomatic bulbar disease and was able to detect this group with an excellent discrimination ability (area under the curve = 0.83). Kinematic analyses revealed associations with expected articulators, greater motor complexity, and differential articulatory patterns for the novel real-word repetitions than their DDK counterparts. Only LAR significantly declined longitudinally over the disease course. Conclusion Novel real-word clinimetric rate tasks evaluating tongue and labial articulatory dysfunction are valid and effective markers for early detection and tracking of bulbar disease in ALS.

Speech Rate Mediated Vowel and Stop Voicing Distinctiveness in Parkinson's Disease

Purpose The purpose of this study was to quantify changes in acoustic distinctiveness in two groups of talkers with Parkinson's disease as they modify across a wide range of speaking rates. Method People with Parkinson's disease with and without deep brain stimulation and older healthy controls read 24 carrier phrases at different speech rates. Target nonsense words in the carrier phrases were designed to elicit stop consonants and corner vowels. Participants spoke at seven self-selected speech rates from very slow to very fast, elicited via magnitude production. Speech rate was measured in absolute words per minute and as a proportion of each talker's habitual rate. Measures of segmental distinctiveness included a temporal consonant measure, namely, voice onset time, and a spectral vowel measure, namely, vowel articulation index. Results All talkers successfully modified their rate of speech from slow to fast. Talkers with Parkinson's disease and deep brain stimulation demonstrated greater baseline speech impairment and produced smaller proportional changes at the fast end of the continuum. Increasingly slower speaking rates were associated with increased temporal contrasts (voice onset time) but not spectral contrasts (vowel articulation). Faster speech was associated with decreased contrasts in both domains. Talkers with deep brain stimulation demonstrated more aberrant productions across all speaking rates. Conclusions Findings suggest that temporal and spectral segmental distinctiveness are asymmetrically affected by speaking rate modifications in Parkinson's disease. Talkers with deep brain stimulation warrant further investigation with regard to speech changes they make as they adjust their speaking rate.

Using Data Augmentation and Time-Scale Modification to Improve ASR of Children’s Speech in Noisy Environments

Current ASR systems show poor performance in recognition of children’s speech in noisy environments because recognizers are typically trained with clean adults’ speech and therefore there are two mismatches between training and testing phases (i.e., clean speech in training vs. noisy speech in testing and adult speech in training vs. child speech in testing). This article studies methods to tackle the effects of these two mismatches in recognition of noisy children’s speech by investigating two techniques: data augmentation and time-scale modification. In the former, clean training data of adult speakers are corrupted with additive noise in order to obtain training data that better correspond to the noisy testing conditions. In the latter, the fundamental frequency (F0) and speaking rate of children’s speech are modified in the testing phase in order to reduce differences in the prosodic characteristics between the testing data of child speakers and the training data of adult speakers. A standard ASR system based on DNN–HMM was built and the effects of data augmentation, F0 modification, and speaking rate modification on word error rate (WER) were evaluated first separately and then by combining all three techniques. The experiments were conducted using children’s speech corrupted with additive noise of four different noise types in four different signal-to-noise (SNR) categories. The results show that the combination of all three techniques yielded the best ASR performance. As an example, the WER value averaged over all four noise types in the SNR category of 5 dB dropped from 32.30% to 12.09% when the baseline system, in which no data augmentation or time-scale modification were used, was replaced with a recognizer that was built using a combination of all three techniques. In summary, in recognizing noisy children’s speech with ASR systems trained with clean adult speech, considerable improvements in the recognition performance can be achieved by combining data augmentation based on noise addition in the system training phase and time-scale modification based on modifying F0 and speaking rate of children’s speech in the testing phase.

The effects of therapeutic group singing on voice, cough and quality of life in parkinson’s disease

Purpose: To examine the effect of a group therapeutic singing intervention on voice, cough, and quality of life in persons with Parkinson Disease (PD) in a community-based outpatient setting using a repeated measures design.Methods: 19 volunteer participants with PD completed the study. Ten participants participated in the intervention and nine served voluntarily as controls. Participants completed one hour group singing sessions over 12 weeks led by a music therapist. Sessions consisted of 30 min of high intensity vocal exercise and 15 to 20 minutes of group singing. Data on phonation, speech, cough, and quality of life were collected pre-intervention and one week post intervention with final data collection 12 weeks post-intervention.Results: No significant change in voice measures although 50% of participants showed improvement. A main effect was found for breathiness (p=0.023), appropriate pitch level (p=0.037) and speaking rate (p=0.009). No main effect for cough but pairwise comparisons were nearly significant pre to post intervention (p=0.053) and pre-intervention to final follow up (p=0.023). No main effect found for QOL but singing participants demonstrated better QOL scores than controls.Conclusions: Results from this small sample suggest that there are some speech benefits from singing intervention as well as potential improvement in cough for airway clearance. Additional study is needed to confirm these results.