Spoken Language Alterations can Predict Phenoconversion in Isolated Rapid Eye Movement Sleep Behavior Disorder: A Multicenter Study.

OBJECTIVE: This study assessed the relationship between speech and language impairment and outcome in a multicenter cohort of isolated/idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD). METHODS: Patients with iRBD from 7 centers speaking Czech, English, German, French, and Italian languages underwent a detailed speech assessment at baseline. Story-tale narratives were transcribed and linguistically annotated using fully automated methods based on automatic speech recognition and natural language processing algorithms, leading to the 3 distinctive linguistic and 2 acoustic patterns of language deterioration and associated composite indexes of their overall severity. Patients were then prospectively followed and received assessments for parkinsonism or dementia during follow-up. The Cox proportional hazard was performed to evaluate the predictive value of language patterns for phenoconversion over a follow-up period of 5 years. RESULTS: Of 180 patients free of parkinsonism or dementia, 156 provided follow-up information. After a mean follow-up of 2.7 years, 42 (26.9%) patients developed neurodegenerative disease. Patients with higher severity of linguistic abnormalities (hazard ratio [HR = 2.35]) and acoustic abnormalities (HR = 1.92) were more likely to develop a defined neurodegenerative disease, with converters having lower content richness (HR = 1.74), slower articulation rate (HR = 1.58), and prolonged pauses (HR = 1.46). Dementia-first (n = 16) and parkinsonism-first with mild cognitive impairment (n = 9) converters had higher severity of linguistic abnormalities than parkinsonism-first with normal cognition converters (n = 17). INTERPRETATION: Automated language analysis might provide a predictor of phenoconversion from iRBD into synucleinopathy subtypes with cognitive impairment, and thus can be used to stratify patients for neuroprotective trials. ANN NEUROL 2024;95:530-543.

Automated Vowel Articulation Analysis in Connected Speech Among Progressive Neurological Diseases, Dysarthria Types, and Dysarthria Severities.

PURPOSE: Although articulatory impairment represents distinct speech characteristics in most neurological diseases affecting movement, methods allowing automated assessments of articulation deficits from the connected speech are scarce. This study aimed to design a fully automated method for analyzing dysarthria-related vowel articulation impairment and estimate its sensitivity in a broad range of neurological diseases and various types and severities of dysarthria. METHOD: Unconstrained monologue and reading passages were acquired from 459 speakers, including 306 healthy controls and 153 neurological patients. The algorithm utilized a formant tracker in combination with a phoneme recognizer and subsequent signal processing analysis. RESULTS: Articulatory undershoot of vowels was presented in a broad spectrum of progressive neurodegenerative diseases, including Parkinson's disease, progressive supranuclear palsy, multiple-system atrophy, Huntington's disease, essential tremor, cerebellar ataxia, multiple sclerosis, and amyotrophic lateral sclerosis, as well as in related dysarthria subtypes including hypokinetic, hyperkinetic, ataxic, spastic, flaccid, and their mixed variants. Formant ratios showed a higher sensitivity to vowel deficits than vowel space area. First formants of corner vowels were significantly lower for multiple-system atrophy than cerebellar ataxia. Second formants of vowels /a/ and /i/ were lower in ataxic compared to spastic dysarthria. Discriminant analysis showed a classification score of up to 41.0% for disease type, 39.3% for dysarthria type, and 49.2% for dysarthria severity. Algorithm accuracy reached an F-score of 0.77. CONCLUSIONS: Distinctive vowel articulation alterations reflect underlying pathophysiology in neurological diseases. Objective acoustic analysis of vowel articulation has the potential to provide a universal method to screen motor speech disorders. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.23681529.

The automated screening of speech motor development in children based on the sequential motion rate.

BACKGROUND: Motor skills in children have traditionally been examined via challenging speech tasks such as syllable repetition, and calculating the syllabic rate using a stopwatch or by inspecting the oscillogram followed by a laborious comparison of the scores on a look-up table representing the typical performances of children of the given age and sex. As the commonly used performance tables are over-simplified to allow for manual scoring, we raise the question of whether a computational model of motor skills development could be more informative, and could allow for the automated screening of children to detect underdeveloped motor skills. METHODS: We recruited a total of 275 children aged four to 15 years. All the participants were native Czech speakers with no history of hearing or neurological impairments. We recorded each child's performance of/pa/-/ta/-/ka/syllable repetition. Various parameters of diadochokinesis (DDK; DDK rate, DDK regularity, voice onset time [VOT] ratio, syllable, vowel and VOT duration) were investigated in the acoustic signals using supervised reference labels. Female and male participants were analyzed separately by comparing younger, middle, and older age groups of children via ANOVA. Finally, we implemented a fully automated model that estimated the developmental age of a child based on the acoustic signal, and evaluated its accuracy using Pearson's correlation coefficient and normalized root-mean-squared errors (RMSEs). RESULTS: The DDK rate reflected the ages of the children proportionally (p < 0.001). Other DDK parameters also showed strong sensitivity to age (p < 0.001), with the exception of VOT duration, which had a smaller effect (p = 0.091). The effect of age was found to be sex specific for the syllable length (p < 0.001) and DDK rate (p = 0.003). We observed that females spoke more slowly and had a longer VOT at preschool age (p < 0.001). The DDK rate obtained via the automated algorithm was strongly correlated with the reference (p < 0.001, Pearson's correlation coefficient of 0.97), with a low normalized RMSE of 3.77%. CONCLUSIONS: As children develop their motor skills, they are capable of shortening the vowels to increase the rate of syllabic repetitions. The nonlinear development in childhood and adolescence, with a steady state in adulthood, follows a logistic function for the DDK rate. This study demonstrates that the development of motor skills can be examined sensitively and more appropriately by a fully automated noninvasive procedure that also accounts for the dispersion of values within age brackets.

Lexical and syntactic deficits analyzed via automated natural language processing: the new monitoring tool in multiple sclerosis.

Background: Impairment of higher language functions associated with natural spontaneous speech in multiple sclerosis (MS) remains underexplored. Objectives: We presented a fully automated method for discriminating MS patients from healthy controls based on lexical and syntactic linguistic features. Methods: We enrolled 120 MS individuals with Expanded Disability Status Scale ranging from 1 to 6.5 and 120 age-, sex-, and education-matched healthy controls. Linguistic analysis was performed with fully automated methods based on automatic speech recognition and natural language processing techniques using eight lexical and syntactic features acquired from the spontaneous discourse. Fully automated annotations were compared with human annotations. Results: Compared with healthy controls, lexical impairment in MS consisted of an increase in content words (p = 0.037), a decrease in function words (p = 0.007), and overuse of verbs at the expense of noun (p = 0.047), while syntactic impairment manifested as shorter utterance length (p = 0.002), and low number of coordinate clause (p < 0.001). A fully automated language analysis approach enabled discrimination between MS and controls with an area under the curve of 0.70. A significant relationship was detected between shorter utterance length and lower symbol digit modalities test score (r = 0.25, p = 0.008). Strong associations between a majority of automatically and manually computed features were observed (r > 0.88, p < 0.001). Conclusion: Automated discourse analysis has the potential to provide an easy-to-implement and low-cost language-based biomarker of cognitive decline in MS for future clinical trials.

Speech and gait abnormalities in motor subtypes of de-novo Parkinson's disease.

AIM: To investigate the presence and relationship of temporal speech and gait parameters in patients with postural instability/gait disorder (PIGD) and tremor-dominant (TD) motor subtypes of Parkinson's disease (PD). METHODS: Speech samples and instrumented walkway system assessments were acquired from a total of 60 de-novo PD patients (40 in TD and 20 in PIGD subtype) and 40 matched healthy controls. Objective acoustic vocal assessment of seven distinct speech timing dimensions was related to instrumental gait measures including velocity, cadence, and stride length. RESULTS: Compared to controls, PIGD subtype showed greater consonant timing abnormalities by prolonged voice onset time (VOT) while also shorter stride length during both normal walking and dual task, while decreased velocity and cadence only during dual task. Speaking rate was faster in PIGD than TD subtype. In PIGD subtype, prolonged VOT correlated with slower gait velocity (r = -0.56, p = 0.01) and shorter stride length (r = -0.59, p = 0.008) during normal walking, whereas relationships were also found between decreased cadence in dual task and irregular alternating motion rates (r = -0.48, p = 0.04) and prolonged pauses (r = -0.50, p = 0.03). No correlation between speech and gait was detected in TD subtype. CONCLUSION: Our findings suggest that speech and gait rhythm disorder share similar underlying pathomechanisms specific for PIGD subtype.

Speech biomarkers in Huntington's disease: A cross-sectional study in pre-symptomatic, prodromal and early manifest stages.

BACKGROUND AND PURPOSE: Motor speech alterations are a prominent feature of clinically manifest Huntington's disease (HD). Objective acoustic analysis of speech can quantify speech alterations. It is currently unknown, however, at what stage of HD speech alterations can be reliably detected. We aimed to explore the patterns and extent of speech alterations using objective acoustic analysis in HD and to assess correlations with both rater-assessed phenotypical features and biological determinants of HD. METHODS: Speech samples were acquired from 44 premanifest (29 pre-symptomatic and 15 prodromal) and 25 manifest HD gene expansion carriers, and 25 matched healthy controls. A quantitative automated acoustic analysis of 10 speech dimensions was performed. RESULTS: Automated speech analysis allowed us to differentiate between participants with HD and controls, with areas under the curve of 0.74 for pre-symptomatic, 0.92 for prodromal, and 0.97 for manifest stages. In addition to irregular alternating motion rates and prolonged pauses seen only in manifest HD, both prodromal and manifest HD displayed slowed articulation rate, slowed alternating motion rates, increased loudness variability, and unstable steady-state position of articulators. In participants with premanifest HD, speech alteration severity was associated with cognitive slowing (r = -0.52, p < 0.001) and the extent of bradykinesia (r = 0.43, p = 0.004). Speech alterations correlated with a measure of exposure to mutant gene products (CAG-age-product score; r = 0.60, p < 0.001). CONCLUSION: Speech abnormalities in HD are associated with other motor and cognitive deficits and are measurable already in premanifest stages of HD. Therefore, automated speech analysis might represent a quantitative HD biomarker with potential for assessing disease progression.

Long-Term Averaged Spectrum Descriptors of Dysarthria in Patients With Parkinson's Disease Treated With Subthalamic Nucleus Deep Brain Stimulation.

PURPOSE: This study aimed to evaluate whether long-term averaged spectrum (LTAS) descriptors for reading and monologue are suitable to detect worsening of dysarthria in patients with Parkinson's disease (PD) treated with subthalamic nucleus deep brain stimulation (STN-DBS) with potential effect of ON and OFF stimulation conditions and types of connected speech. METHOD: Four spectral moments based on LTAS were computed for monologue and reading passage collected from 23 individuals with PD treated with bilateral STN-DBS and 23 age- and gender-matched healthy controls. Speech performance of patients with PD was compared in ON and OFF STN-DBS conditions. RESULTS: All LTAS spectral moments including mean, standard deviation, skewness, and kurtosis across both monologue and reading passage were able to significantly distinguish between patients with PD in both stimulation conditions and control speakers. The spectral mean was the only LTAS measure sensitive to capture better speech performance in STN-DBS ON, as compared to the STN-DBS OFF stimulation condition (p < .05). Standardized reading passage was more sensitive compared to monologue in detecting dysarthria severity via LTAS descriptors with an area under the curve of up to 0.92 obtained between PD and control groups. CONCLUSIONS: Our findings confirmed that LTAS is a suitable approach to objectively describe changes in speech impairment severity due to STN-DBS therapy in patients with PD. We envisage these results as an important step toward a continuum development of technological solutions for the automated assessment of stimulation-induced dysarthria. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.21644798.

Articulatory undershoot of vowels in isolated REM sleep behavior disorder and early Parkinson's disease.

Imprecise vowels represent a common deficit associated with hypokinetic dysarthria resulting from a reduced articulatory range of motion in Parkinson's disease (PD). It is not yet unknown whether the vowel articulation impairment is already evident in the prodromal stages of synucleinopathy. We aimed to assess whether vowel articulation abnormalities are present in isolated rapid eye movement sleep behaviour disorder (iRBD) and early-stage PD. A total of 180 male participants, including 60 iRBD, 60 de-novo PD and 60 age-matched healthy controls performed reading of a standardized passage. The first and second formant frequencies of the corner vowels /a/, /i/, and /u/ extracted from predefined words, were utilized to construct articulatory-acoustic measures of Vowel Space Area (VSA) and Vowel Articulation Index (VAI). Compared to controls, VSA was smaller in both iRBD (p = 0.01) and PD (p = 0.001) while VAI was lower only in PD (p = 0.002). iRBD subgroup with abnormal olfactory function had smaller VSA compared to iRBD subgroup with preserved olfactory function (p = 0.02). In PD patients, the extent of bradykinesia and rigidity correlated with VSA (r = -0.33, p = 0.01), while no correlation between axial gait symptoms or tremor and vowel articulation was detected. Vowel articulation impairment represents an early prodromal symptom in the disease process of synucleinopathy. Acoustic assessment of vowel articulation may provide a surrogate marker of synucleinopathy in scenarios where a single robust feature to monitor the dysarthria progression is needed.

Speech acoustic indices for differential diagnosis between Parkinson's disease, multiple system atrophy and progressive supranuclear palsy.

While speech disorder represents an early and prominent clinical feature of atypical parkinsonian syndromes such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), little is known about the sensitivity of speech assessment as a potential diagnostic tool. Speech samples were acquired from 215 subjects, including 25 MSA, 20 PSP, 20 Parkinson's disease participants, and 150 healthy controls. The accurate differential diagnosis of dysarthria subtypes was based on the quantitative acoustic analysis of 26 speech dimensions related to phonation, articulation, prosody, and timing. A semi-supervised weighting-based approach was then applied to find the best feature combinations for separation between PSP and MSA. Dysarthria was perceptible in all PSP and MSA patients and consisted of a combination of hypokinetic, spastic, and ataxic components. Speech features related to respiratory dysfunction, imprecise consonants, monopitch, slow speaking rate, and subharmonics contributed to worse performance in PSP than MSA, whereas phonatory instability, timing abnormalities, and articulatory decay were more distinctive for MSA compared to PSP. The combination of distinct speech patterns via objective acoustic evaluation was able to discriminate between PSP and MSA with very high accuracy of up to 89% as well as between PSP/MSA and PD with up to 87%. Dysarthria severity in MSA/PSP was related to overall disease severity. Speech disorders reflect the differing underlying pathophysiology of tauopathy in PSP and α-synucleinopathy in MSA. Vocal assessment may provide a low-cost alternative screening method to existing subjective clinical assessment and imaging diagnostic approaches.

Linguistic Abnormalities in Isolated Rapid Eye Movement Sleep Behavior Disorder.

BACKGROUND: Patients with synucleinopathies frequently display language abnormalities. However, whether patients with isolated rapid eye movement sleep behavior disorder (iRBD) have prodromal language impairment remains unknown. OBJECTIVE: We examined whether the linguistic abnormalities in iRBD can serve as potential biomarkers for conversion to synucleinopathy, including the possible effect of mild cognitive impairment (MCI), speaking task, and automation of analysis procedure. METHODS: We enrolled 139 Czech native participants, including 40 iRBD without MCI and 14 iRBD with MCI, compared with 40 PD without MCI, 15 PD with MCI, and 30 healthy control subjects. Spontaneous discourse and story-tale narrative were transcribed and linguistically annotated. A quantitative analysis was performed computing three linguistic features. Human annotations were compared with fully automated annotations. RESULTS: Compared with control subjects, patients with iRBD showed poorer content density, reflecting the reduction of content words and modifiers. Both PD and iRBD subgroups with MCI manifested less occurrence of unique words and a higher number of n-grams repetitions, indicating poorer lexical richness. The spontaneous discourse task demonstrated language impairment in iRBD without MCI with an area under the curve of 0.72, while the story-tale narrative task better reflected the presence of MCI, discriminating both PD and iRBD subgroups with MCI from control subjects with an area under the curve of up to 0.81. A strong correlation between manually and automatically computed results was achieved. CONCLUSIONS: Linguistic features might provide a reliable automated method for detecting cognitive decline caused by prodromal neurodegeneration in subjects with iRBD, providing critical outcomes for future therapeutic trials. © 2022 International Parkinson and Movement Disorder Society.

Automated video-based assessment of facial bradykinesia in de-novo Parkinson's disease.

Even though hypomimia is a hallmark of Parkinson's disease (PD), objective and easily interpretable tools to capture the disruption of spontaneous and deliberate facial movements are lacking. This study aimed to develop a fully automatic video-based hypomimia assessment tool and estimate the prevalence and characteristics of hypomimia in de-novo PD patients with relation to clinical and dopamine transporter imaging markers. For this cross-sectional study, video samples of spontaneous speech were collected from 91 de-novo, drug-naïve PD participants and 75 age and sex-matched healthy controls. Twelve facial markers covering areas of forehead, nose root, eyebrows, eyes, lateral canthal areas, cheeks, mouth, and jaw were used to quantitatively describe facial dynamics. All patients were evaluated using Movement Disorder Society-Unified PD Rating Scale and Dopamine Transporter Single-Photon Emission Computed Tomography. Newly developed automated facial analysis tool enabled high-accuracy discrimination between PD and controls with area under the curve of 0.87. The prevalence of hypomimia in de-novo PD cohort was 57%, mainly associated with dysfunction of mouth and jaw movements, and decreased variability in forehead and nose root wrinkles (p < 0.001). Strongest correlation was found between reduction of lower lip movements and nigro-putaminal dopaminergic loss (r = 0.32, p = 0.002) as well as limb bradykinesia/rigidity scores (r = -0.37 p < 0.001). Hypomimia represents a frequent, early marker of motor impairment in PD that can be robustly assessed via automatic video-based analysis. Our results support an association between striatal dopaminergic deficit and hypomimia in PD.

Toward Automated Articulation Rate Analysis via Connected Speech in Dysarthrias.

PURPOSE: This study aimed to evaluate the reliability of different approaches for estimating the articulation rates in connected speech of Parkinsonian patients with different stages of neurodegeneration compared to healthy controls. METHOD: Monologues and reading passages were obtained from 25 patients with idiopathic rapid eye movement sleep behavior disorder (iRBD), 25 de novo patients with Parkinson's disease (PD), 20 patients with multiple system atrophy (MSA), and 20 healthy controls. The recordings were subsequently evaluated using eight syllable localization algorithms, and their performances were compared to a manual transcript used as a reference. RESULTS: The Google & Pyphen method, based on automatic speech recognition followed by hyphenation, outperformed the other approaches (automated vs. hand transcription: r > .87 for monologues and r > .91 for reading passages, p < .001) in precise feature estimates and resilience to dysarthric speech. The Praat script algorithm achieved sufficient robustness (automated vs. hand transcription: r > .65 for monologues and r > .78 for reading passages, p < .001). Compared to the control group, we detected a slow rate in patients with MSA and a tendency toward a slower rate in patients with iRBD, whereas the articulation rate was unchanged in patients with early untreated PD. CONCLUSIONS: The state-of-the-art speech recognition tool provided the most precise articulation rate estimates. If speech recognizer is not accessible, the freely available Praat script based on simple intensity thresholding might still provide robust properties even in severe dysarthria. Automated articulation rate assessment may serve as a natural, inexpensive biomarker for monitoring disease severity and a differential diagnosis of Parkinsonism.

Short-term effect of dopaminergic medication on speech in early-stage Parkinson's disease.

The effect of dopaminergic medication on speech has rarely been examined in early-stage Parkinson's disease (PD) and the respective literature is inconclusive and limited by inappropriate design with lack of PD control group. The study aims to examine the short-term effect of dopaminergic medication on speech in PD using patients with good motor responsiveness to levodopa challenge compared to a control group of PD patients with poor motor responsiveness. A total of 60 early-stage PD patients were investigated before (OFF) and after (ON) acute levodopa challenge and compared to 30 age-matched healthy controls. PD patients were categorised into two clinical subgroups (PD responders vs. PD nonresponders) according to the comparison of their motor performance based on movement disorder society-unified Parkinson's disease rating scale, part III. Seven distinctive parameters of hypokinetic dysarthria were examined using quantitative acoustic analysis. We observed increased monopitch (p > 0.01), aggravated monoloudness (p > 0.05) and longer duration of stop consonants (p > 0.05) in PD compared to healthy controls, confirming the presence of hypokinetic dysarthria in early PD. No speech alterations from OFF to ON state were revealed in any of the two PD groups and speech dimensions investigated including monopitch, monoloudness, imprecise consonants, harsh voice, slow sequential motion rates, articulation rate, or inappropriate silences, although a subgroup of PD responders manifested obvious improvement in motor function after levodopa intake (p > 0.001). Since the short-term usage of levodopa does not easily affect voice and speech performance in PD, speech assessment may provide a medication state-independent motor biomarker of PD.

Dysprosody in Isolated REM Sleep Behavior Disorder with Impaired Olfaction but Intact Nigrostriatal Pathway.

BACKGROUND: Impairments of olfactory and speech function are likely early prodromal symptoms of α-synucleinopathy. OBJECTIVE: The aim of this study is to assess whether dysprosody is present in isolated rapid eye movement sleep behavior disorder (iRBD) with hyposmia/anosmia and a normal nigrostriatal system. METHODS: Pitch variability during speech was investigated in 17 iRBD subjects with normal olfactory function (iRBD-NOF), 30 iRBD subjects with abnormal olfactory function (iRBD-AOF), and 50 healthy controls. iRBD subjects were evaluated using the University of Pennsylvania Smell Identification Test and [123I]-2ß-carbomethoxy-3ß-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane dopamine transporter single-photon emission computed tomography (DAT-SPECT). All iRBD subjects completed the 24-month follow-up with DAT-SPECT, speech, and olfactory testing. RESULTS: At baseline, only iRBD-AOF showed monopitch when compared to iRBD-NOF (P = 0.04) and controls (P = 0.03), with no difference between iRBD-NOF and controls (P = 1). At follow-up, dysprosody progressed only in iRBD-AOF with abnormal DAT-SPECT (P = 0.03). CONCLUSION: Prosody is impaired in hyposmic but not in normosmic iRBD subjects before the nigrostriatal dopaminergic transmission is affected (Braak stage 2). © 2021 International Parkinson and Movement Disorder Society.

Automated speech analysis in early untreated Parkinson's disease: Relation to gender and dopaminergic transporter imaging.

BACKGROUND: The mechanisms underlying speech abnormalities in Parkinson's disease (PD) remain poorly understood, with most of the available evidence based on male patients. This study aimed to estimate the occurrence and characteristics of speech disorder in early, drug-naive PD patients with relation to gender and dopamine transporter imaging. METHODS: Speech samples from 60 male and 40 female de novo PD patients as well as 60 male and 40 female age-matched healthy controls were analyzed. Quantitative acoustic vocal assessment of 10 distinct speech dimensions related to phonation, articulation, prosody, and speech timing was performed. All patients were evaluated using [123]I-2b-carbomethoxy-3b-(4-iodophenyl)-N-(3-fluoropropyl) nortropane single-photon emission computed tomography and Montreal Cognitive Assessment. RESULTS: The prevalence of speech abnormalities in the de novo PD cohort was 56% for male and 65% for female patients, mainly manifested with monopitch, monoloudness, and articulatory decay. Automated speech analysis enabled discrimination between PD and controls with an area under the curve of 0.86 in men and 0.93 in women. No gender-specific speech dysfunction in de novo PD was found. Regardless of disease status, females generally showed better performance in voice quality, consonant articulation, and pauses production than males, who were better only in loudness variability. The extent of monopitch was correlated to nigro-putaminal dopaminergic loss in men (r = 0.39, p = 0.003) and the severity of imprecise consonants was related to cognitive deficits in women (r = -0.44, p = 0.005). CONCLUSIONS: Speech abnormalities represent a frequent and early marker of motor abnormalities in PD. Despite some gender differences, our findings demonstrate that speech difficulties are associated with nigro-putaminal dopaminergic deficits.

Distinct patterns of speech disorder in early-onset and late-onset de-novo Parkinson's disease.

Substantial variability and severity of dysarthric patterns across Parkinson's disease (PD) patients may reflect distinct phenotypic differences. We aimed to compare patterns of speech disorder in early-onset PD (EOPD) and late-onset PD (LOPD) in drug-naive patients at early stages of disease. Speech samples were acquired from a total of 96 participants, including two subgroups of 24 de-novo PD patients and two subgroups of 24 age- and sex-matched young and old healthy controls. The EOPD group included patients with age at onset below 51 (mean 42.6, standard deviation 6.1) years and LOPD group patients with age at onset above 69 (mean 73.9, standard deviation 3.0) years. Quantitative acoustic vocal assessment of 10 unique speech dimensions related to respiration, phonation, articulation, prosody, and speech timing was performed. Despite similar perceptual dysarthria severity in both PD subgroups, EOPD showed weaker inspirations (p = 0.03), while LOPD was characterized by decreased voice quality (p = 0.02) and imprecise consonant articulation (p = 0.03). In addition, age-independent occurrence of monopitch (p < 0.001), monoloudness (p = 0.008), and articulatory decay (p = 0.04) was observed in both PD subgroups. The worsening of consonant articulation was correlated with the severity of axial gait symptoms (r = 0.38, p = 0.008). Speech abnormalities in EOPD and LOPD share common features but also show phenotype-specific characteristics, likely reflecting the influence of aging on the process of neurodegeneration. The distinct pattern of imprecise consonant articulation can be interpreted as an axial motor symptom of PD.

Defining Speech Subtypes in De Novo Parkinson Disease: Response to Long-term Levodopa Therapy.

BACKGROUND AND OBJECTIVES: Patterns of speech disorder in Parkinson disease (PD), which are highly variable across individual patients, have not been systematically studied. Our aim was to identify speech subtypes in treatment-naive patients with PD and to examine their response to long-term dopaminergic therapy. METHODS: We recorded speech data from a total of 111 participants with de novo PD; 83 of the participants completed the 12-month follow-up (69 patients with PD on stable dopaminergic medication and 14 untreated controls with PD). Unsupervised k-means cluster analysis was performed on 8 distinctive parameters of hypokinetic dysarthria examined with quantitative acoustic analysis. RESULTS: Three distinct speech subtypes with similar prevalence, symptom duration, and motor severity were detected: prosodic, phonatory-prosodic, and articulatory-prosodic. Besides monopitch and monoloudness, which were common in each subtype, speech impairment was more severe in the phonatory-prosodic subtype with predominant dysphonia and the articulatory-prosodic subtype with predominant imprecise consonant articulation than in the prosodic subtype. Clinically, the prosodic subtype was characterized by a prevalence of women and younger age, while articulatory-prosodic subtype was characterized by the prevalence of men, older age, greater severity of axial gait symptoms, and poorer cognitive performance. The phonatory-prosodic subtype clinically represented intermediate status in age with mostly men and preserved cognitive performance. While speech of untreated controls with PD deteriorated over 1 year (p = 0.02), long-term dopaminergic medication maintained stable speech impairment severity in the prosodic and articulatory-prosodic subtypes and improved speech performance in patients with the phonatory-prosodic subtype (p = 0.002). DISCUSSION: Distinct speech phenotypes in de novo PD reflect divergent underlying mechanisms and allow prediction of response of speech impairment to levodopa therapy. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, in patients with newly diagnosed PD with speech impairment, speech phenotype is associated with levodopa responsiveness.

Effect of reading passage length on quantitative acoustic speech assessment in Czech-speaking individuals with Parkinson's disease treated with subthalamic nucleus deep brain stimulation.

Little is known about the minimum sample length required for the stable acoustic assessment of speech in Parkinson's disease (PD). This study aimed to investigate the effect of the duration of the reading passage on the determination of reliable acoustic patterns in individuals with PD treated with subthalamic nucleus deep brain stimulation. A phonetically balanced reading text of 313 words was collected from 32 Czech persons with PD, and 32 age- and sex-matched healthy controls. The reading passage was segmented to produce ten sub-texts of increasing length ranging from a one- to a ten-segment-long sub-text. An error rate analysis was used to estimate the required stabilization value by evaluating the differences between the sub-texts and the entire text across seven hypokinetic dysarthria features. The minimum length of a reading passage equal to 128 words was found to be necessary for acoustic assessment, with similar lengths being required for the controls (120 words) and the two PD subgroups, including Parkinsonian individuals with a mild (126 words) and moderate (128 words) dysarthria severity. The current study provides important guidelines for the necessary sample length for future expert instrumental dysarthria assessments and assists in decreasing the time required for clinical speech evaluations.