Utianski, Rene L

Purpose: This study examined whether phoneme-level posterior probabilities generated by an articulatory-informed deep learning model (Phonet) can serve as interpretable and sensitive markers of articulatory impairment in motor speech disorders (MSDs). The goal was to determine whether these features distinguish individuals with and without MSDs and reflect varying severity levels of articulatory impairment. Method: A total of 676 participants (199 with MSDs, 477 without MSDs) completed a remotely captured word repetition task. Speech recordings were phonetically aligned, and posterior probabilities were extracted using a retrained version of the Phonet model, which estimates frame-level probabilities for 23 phonological classes. Segment-level posterior values were computed and compared across groups and severity levels using linear mixed-effects regression models. Results: Posterior probabilities were significantly reduced in the MSD group across all phoneme types. Within the MSD group, posterior probabilities decreased progressively with greater clinical severity, as measured by both perceptual sound distortion ratings and a cumulative articulation error score. Segment-specific analyses revealed systematic differences across phoneme classes, indicating that posterior probabilities capture distinct patterns of articulatory degradation associated with motor speech impairment. Conclusions: Phoneme-level posterior probabilities serve as interpretable, segment-specific indicators of articulatory impairment in MSDs. These features differentiate clinical status and reflect gradations of severity, making them promising tools for augmenting traditional perceptual speech assessments. Their linguistic transparency and scalability support future clinical applications in diagnosis, monitoring, and targeted intervention.

Purpose: Frontotemporal lobar degeneration (FTLD) is the neuropathology that underlies a collection of progressive clinical syndromes typically classified by the initial/primary symptom. For example, individuals with loss of word meaning as a first manifestation are often diagnosed with the semantic variant of primary progressive aphasia. Growing evidence suggests that language and communication can be impacted in all clinical syndromes across the FTLD spectrum, but the functional relevance of these symptoms has yet to be explored. Method: The Frontotemporal Degeneration (FTD) Insights Survey is the largest community survey of individuals affected by FTLD. It was administered online and included questions related to demographics, symptoms, life participation, quality of life, and experiences with and hopes for treatment. Self-reported diagnoses of respondents included the nonfluent/agrammatic, semantic, and unspecified variants of primary progressive aphasia, semantic dementia, corticobasal syndrome, progressive supranuclear palsy, and behavioral variant FTD. Here, we grouped respondents according to whether they had a language-predominant ( n = 43), motor-predominant ( n = 43), or behavior-predominant ( n = 90) variant of FTLD and used descriptive statistics to explore how they perceive their own communication difficulties and gauge their motivation for management. Results: Over 65% of respondents in each group identified changes to communication as a symptom; subsequent analyses focused on the responses of this cohort. Across groups, word finding and speaking were two of the most frequently endorsed difficulties. Over 50% of each group identified improved communication as a treatment priority, reflecting the impact that these symptoms have on their day-to-day life. Speech-language therapy is an important approach to manage these changes and minimize their impact. Whereas 76% of the language and motor groups had attended speech-language therapy, this was true for only 16% of the behavior group. Conclusions: Individuals across the FTLD spectrum experience changes to communication that impact their social engagement and quality of life. Management needs to be tailored to the needs of each individual, but recommendations are provided based on the insights and group-level preferences reported here. Future research is needed to identify current referral practices and how to increase engagement in skilled communication interventions, especially for individuals with the behavioral variant of FTD. Supplemental Material: https://doi.org/10.23641/asha.33940597

Abstract Purpose To evaluate whether two automated measures of nasality, Nasal Cognate Distinctiveness (NCD) and nasal posterior probability (NPP), provide clinically meaningful markers of hypernasality in speakers with motor speech disorders (MSDs) and to determine whether hypernasality-related information extends beyond stop consonants, which are typically targeted in cognate-based approaches. Method Sentence-level speech recordings were obtained from 561 patients, including 374 neurologically typical controls and 187 individuals with MSDs. NCD was computed for voiceless stops (/p/, /t/, /k/) using likelihood ratios between stops and their nasal cognates. NPP was extracted using a phonological feature-based neural network model and analyzed for stops, consonants, and vowels. Hypernasality severity was rated by speech-language pathologists. Group differences and associations with hypernasality severity were evaluated using linear mixed-effects models and Spearman correlations, and receiver operating characteristic (ROC) analyses were used to evaluate discrimination of absent versus present hypernasality. An additional 20 controls with repeat recordings were used to evaluate test-retest reliability and minimal detectable change (MDC). Results NCD generally decreased and NPP increased with increasing hypernasality severity, with phoneme-specific severity effects observed for NCD. Across stops, NCD and NPP were strongly inversely correlated and showed comparable discrimination of absent versus present hypernasality (AUCs = 0.796 and 0.730, respectively). Consonant and vowel NPP measures were both positively associated with hypernasality severity and demonstrated identical classification performance (AUC = 0.853). No significant differences in ROC performance were observed between NCD and NPP or between consonant and vowel NPP measures. Test-retest change exceeded the MDC threshold in 2 of 20 controls for NCD and 1 of 20 for NPP. Conclusions Both NCD and NPP provide objective markers of hypernasality in speakers with MSDs. The measures capture related aspects of nasalization and demonstrate comparable ability to identify clinically meaningful hypernasality. NPP captures hypernasality-related acoustic information across both consonants and vowels, with similar relationships to severity and classification performance across sound classes. Test-retest findings provide preliminary MDC benchmarks for interpreting longitudinal change.

Purpose: This study aimed to evaluate how speech signal compression algorithms affect the acoustic and perceptual characteristics of dysarthric speech. As telepractice becomes more common in speech-language pathology, particularly in the assessment of dysarthria, understanding the impact of telecommunication compression on speech fidelity is essential for clinical decision making. Method: Speech samples were collected from 15 individuals with dysarthria, recorded locally and simultaneously via Zoom (Version 6.2.11). The Opus codec was used to process the locally recorded speech samples under fullband, wideband, and narrowband compression conditions. Acoustic measures were derived for all samples. Twenty experienced speech-language pathologists (SLPs) rated vocal quality and nasality for sustained vowels and rated articulatory precision and orthographically transcribed sentences across each condition. Results: Narrowband compression was associated with significantly degraded voice quality measures (e.g., harmonic-to-noise ratio, shimmer) and reduced transcription accuracy. Despite these changes in acoustics and intelligibility, ratings of articulatory precision, nasality, and vocal quality remained stable across conditions, suggesting SLPs could adjust for compression artifacts when making perceptual judgments. Conclusions: Speech compression, particularly in low-bandwidth (i.e., narrow) condition, impacts acoustic fidelity and intelligibility, though expert listeners maintain reliable perceptual judgments. These findings underscore the need to consider compression effects in telepractice and highlight the importance of developing optimized protocols for remote dysarthria assessment.

Abstract Motor speech disorders (MSDs) are early markers of neurological disease, but expert perceptual analysis is rarely available outside specialized centers. Automated speech analysis offers a scalable alternative, yet prior studies have not systematically compared modeling approaches or assessed clinically relevant metrics in independent datasets. This study compared static acoustic features, articulatory informed Phonet features, and self-supervised pretrained models for binary and multi label MSD classification. We trained and evaluated models on 583 speech samples using speaker level splits. Baseline models included logistic regression and Gated Recurrent Units (GRUs) trained on eGeMAPS and MFCCs. We extracted three types of Phonet derived features and evaluated pretrained HuBERT and SSAST models in frozen, partially fine-tuned, and fully fine-tuned configurations. Binary classification distinguished MSDs from controls, while multi label classification identified six MSD subtypes. Models were assessed using validation AUC, and cut points were tested on two independent datasets. Pretrained and Phonet based models substantially outperformed static acoustic features. In binary classification, HuBERT achieved the highest AUC (0.95), while compact Phonet derived GRUs achieved comparable performance (up to 0.94). These models generalized well to independent datasets, maintaining high sensitivity (0.94) and specificity (0.97). In multi label classification, Phonet models achieved the highest macro average AUC (0.86), but threshold-based subtype performance declined on unseen data. Automated MSD detection is feasible and clinically promising. Binary classification generalized well, whereas multi label classification showed limited threshold stability across datasets.

Abstract This study examined the extent to which goodness of pronunciation (GoP) scores and phonological posterior probabilities capture perceptual ratings of speech severity in individuals with motor speech disorders (MSD). Speech recordings of the word catastrophe were obtained from 489 participants, including 333 neurologically typical controls and 156 individuals with MSD. GoP scores were derived using traditional acoustic features and self-supervised speech representations, including WavLM and XLS-R, across multiple modeling approaches, while phonological posterior probabilities were extracted using Phonet. Model performance was evaluated using Kendall’s rank correlations, regression, and receiver operating characteristic analyses against speech-language pathologists’ perceptual ratings of sound distortion and intelligibility. Both GoP and phonological posterior probabilities were significantly associated with perceptual ratings. Self-supervised speech representations substantially outperformed traditional acoustic features, with WavLM-based GoP using k-nearest neighbors achieving the strongest performance. Across correlation, regression, and classification analyses, GoP consistently outperformed phonological posterior probabilities for both sound distortion and intelligibility. Age and gender had minimal influence on model-derived measures or their relationships with perceptual ratings. These findings demonstrate the value of self-supervised GoP as an objective measure of speech impairment while highlighting the complementary role of phonological posterior probabilities in characterizing articulatory aspects of motor speech disorders.

Purpose: Significant variation is observed in diagnostic assessments for individuals with acquired apraxia of speech (AOS). The lack of consistency across research related to AOS impacts the comparison of intervention outcomes. This extends to diagnostic criteria, assessment, and the inclusion of patient demographics. This viewpoint examines outcomes related to the consistency in diagnostic tool use and collection of demographic information and introduces a template to support researchers and clinicians conducting diagnostic evaluations. Materials include guidelines for a thorough case history, current diagnostic characteristics, and diagnostic assessment tools available for describing AOS. The template illustrates how such materials can be structured and applied in research and clinical practice. Method: The recommendations provided in this viewpoint are part of a recent systematic review about AOS treatment outcomes. Trained raters extracted data from a comprehensive literature search from 1951 to April 2024 using a consensus protocol. Results: Of the 92 studies included in data extraction, demographic information such as age, gender, etiology, and months post-onset was commonly reported, and information about race and ethnicity (described in 15% of studies), socioeconomic status (0%), current/previous occupation (8%), language history (10%), and education (59%) was described less frequently. Reported diagnostic characteristics varied across studies, reflecting differences in using discriminatory versus nondiscriminatory features. Concomitant diagnoses, such as aphasia severity (37%) and presence of dysarthria (32%), were not consistently reported or described. Conclusion: A template with specific criteria and assessments can support research replication, raise awareness of diagnostic strategies, and offer a structured framework for investigators and clinicians. Supplemental Material: https://doi.org/10.23641/asha.32012346

Purpose: This letter addresses a recent paper by Mailend et al. (2025) that expressed concerns about the Apraxia of Speech Rating Scale (ASRS) and offered guidelines and definitions regarding its principles, scale labels, item definitions, and scoring procedures, including the addition of new items to the scale. The primary purpose of this letter is to clarify the uncertainty that other users of the scale may have about whether the current ASRS version (ASRS 3.5; Duffy et al., 2023) should be altered to include the numerous proposed revisions. It provides examples of proposed revisions that, in our judgment, are helpful, redundant, questionable or premature, or are misaligned with the primary purposes of the scale. Conclusions: Some of the proposed revisions to the ASRS are helpful and likely to improve reliability by reducing user uncertainty about ratings. Others are questionable or premature without supporting data or are not aligned with the primary purposes of the scale.

Purpose: While acquired apraxia of speech (AOS) has been the focus of intervention research for decades, little information is reported about the demographic representation of study participants. This article examines the extent to which published AOS treatment studies report participants' age, sex/gender, race/ethnicity, language background, and socioeconomic status; identifies critical gaps in the literature; and considers implications for representativeness. This information supports the important call to capture these patient factors systematically and thereby advance equity in research and clinical care. Method: This study is part of a larger systematic review examining treatment outcomes for acquired AOS. A comprehensive search of databases from 1951 to April 2024 was completed to determine the proportion of treatment articles that reported demographic information related to diversity. Studies were reviewed by trained raters using a standardized data extraction protocol with a consensus protocol. Results: While participant age and sex/gender were reported in nearly all studies (99% and 100%, respectively), only 24% of studies reported on race/ethnicity, 15% provided information on participants' language background, and none reported socioeconomic status. Among studies that included race/ethnicity, 89% of the participants were White, with minimal representation of other racial/ethnic groups. Conclusions: The underreporting of race/ethnicity, language background, and socioeconomic factors limits the generalizability and ecological validity of AOS treatment research. The field must prioritize inclusive participant recruitment and consistent demographic reporting. We propose a practical template for use in both research and clinical contexts to support more thorough data collection and to inform future work in diagnosis, assessment, and intervention for AOS. Supplemental Material: https://doi.org/10.23641/asha.31172353