Entraining with another person's speech rhythm: Evidence from healthy speakers and individuals with Parkinson's disease

Deep Stroop: Integrating eye tracking and speech processing to characterize people with neurodegenerative disorders while performing neuropsychological tests

Neurodegenerative diseases (NDs) can be difficult to precisely characterize and monitor as they present complex and overlapping signs despite affecting different neural circuits. Neuropsychological tests are important tools for assessing signs, but only considering patient-generated output can limit insight. Here, we present an improvement to the neuropsychological test evaluation paradigm by deeply characterizing patient interaction and behavior during tests based on multiple perspectives alongside typically evaluated output by performing multi-modal analysis of eye movement and speech data. Using the well-known Stroop Test, we compare behaviors of healthy controls to patients with Alzheimer's Disease (AD), Mild Cognitive Impairment, Parkinson's Disease (PD), and secondary Parkinsonism. We maximize accessibility and reproducibility by automatically extracting metrics, including eye motor behavior, speech patterns, and multimodal interplay, with almost no human input required. We find many metrics including increased horizontal saccade distances sensitive to all NDs, delayed task initiation in AD, response error patterns and blinking patterns that differ between AD and PD. Our metrics show both significantly different distributions between disease groups and simultaneous correlation with the MoCA and MDS-UPDRS-III clinical rating scales. Our findings show the utility of incorporating several perspectives into one output representation, as our metric breadth creates unique sign profiles that quantify and visualize a patient's dysfunction. These metrics provide much better sign characterization between diseases and correlation with disease severity than traditional Stroop measures. This methodology offers the potential to expand its application to other traditional neuropsychological tests, shifting the paradigm in diagnostic precision for NDs and advancing patient care.

Speech's syllabic rhythm and articulatory features produced under different auditory feedback conditions identify Parkinsonism

Diagnostic tests for Parkinsonism based on speech samples have shown promising results. Although abnormal auditory feedback integration during speech production and impaired rhythmic organization of speech are known in Parkinsonism, these aspects have not been incorporated into diagnostic tests. This study aimed to identify Parkinsonism using a novel speech behavioral test that involved rhythmically repeating syllables under different auditory feedback conditions. The study included 30 individuals with Parkinson's disease (PD) and 30 healthy subjects. Participants were asked to rhythmically repeat the PA-TA-KA syllable sequence, both whispering and speaking aloud under various listening conditions. The results showed that individuals with PD had difficulties in whispering and articulating under altered auditory feedback conditions, exhibited delayed speech onset, and demonstrated inconsistent rhythmic structure across trials compared to controls. These parameters were then fed into a supervised machine-learning algorithm to differentiate between the two groups. The algorithm achieved an accuracy of 85.4%, a sensitivity of 86.5%, and a specificity of 84.3%. This pilot study highlights the potential of the proposed behavioral paradigm as an objective and accessible (both in cost and time) test for identifying individuals with Parkinson's disease.

Interpretable speech features vs. DNN embeddings: What to use in the automatic assessment of Parkinson's disease in multi-lingual scenarios

Speech-based approaches for assessing Parkinson's Disease (PD) often rely on feature extraction for automatic classification or detection. While many studies prioritize accuracy by using non-interpretable embeddings from Deep Neural Networks, this work aims to explore the predictive capabilities and language robustness of both feature types in a systematic fashion. As interpretable features, prosodic, linguistic, and cognitive descriptors were adopted, while x-vectors, Wav2Vec 2.0, HuBERT, and TRILLsson representations were used as non-interpretable features. Mono-lingual, multi-lingual, and cross-lingual machine learning experiments were conducted leveraging six data sets comprising speech recordings from various languages: American English, Castilian Spanish, Colombian Spanish, Italian, German, and Czech. For interpretable feature-based models, the mean of the best F1-scores obtained from each language was 81% in mono-lingual, 81% in multi-lingual, and 71% in cross-lingual experiments. For non-interpretable feature-based models, instead, they were 85% in mono-lingual, 88% in multi-lingual, and 79% in cross-lingual experiments. Firstly, models based on non-interpretable features outperformed interpretable ones, especially in cross-lingual experiments. Specifically, TRILLsson provided the most stable and accurate results across tasks and data sets. Conversely, the two types of features adopted showed some level of language robustness in multi-lingual and cross-lingual experiments. Overall, these results suggest that interpretable feature-based models can be used by clinicians to evaluate the deterioration of the speech of patients with PD, while non-interpretable feature-based models can be leveraged to achieve higher detection accuracy.

Aberrant neurophysiological signaling associated with speech impairments in Parkinson's disease

Difficulty producing intelligible speech is a debilitating symptom of Parkinson's disease (PD). Yet, both the robust evaluation of speech impairments and the identification of the affected brain systems are challenging. Using task-free magnetoencephalography, we examine the spectral and spatial definitions of the functional neuropathology underlying reduced speech quality in patients with PD using a new approach to characterize speech impairments and a novel brain-imaging marker. We found that the interactive scoring of speech impairments in PD (N = 59) is reliable across non-expert raters, and better related to the hallmark motor and cognitive impairments of PD than automatically-extracted acoustical features. By relating these speech impairment ratings to neurophysiological deviations from healthy adults (N = 65), we show that articulation impairments in patients with PD are associated with aberrant activity in the left inferior frontal cortex, and that functional connectivity of this region with somatomotor cortices mediates the influence of cognitive decline on speech deficits.

Multilingual evaluation of interpretable biomarkers to represent language and speech patterns in Parkinson's disease

Motor impairments are only one aspect of Parkinson's disease (PD), which also include cognitive and linguistic impairments. Speech-derived interpretable biomarkers may help clinicians diagnose PD at earlier stages and monitor the disorder's evolution over time. This study focuses on the multilingual evaluation of a composite array of biomarkers that facilitate PD evaluation from speech. Hypokinetic dysarthria, a motor speech disorder associated with PD, has been extensively analyzed in previously published studies on automatic PD evaluation, with a relative lack of inquiry into language and task variability. In this study, we explore certain acoustic, linguistic, and cognitive information encoded within the speech of several cohorts with PD. A total of 24 biomarkers were analyzed from American English, Italian, Castilian Spanish, Colombian Spanish, German, and Czech by conducting a statistical analysis to evaluate which biomarkers best differentiate people with PD from healthy participants. The study leverages conceptual robustness as a criterion in which a biomarker behaves the same, independent of the language. Hence, we propose a set of speech-based biomarkers that can effectively help evaluate PD while being language-independent. In short, the best acoustic and cognitive biomarkers permitting discrimination between experimental groups across languages were fundamental frequency standard deviation, pause time, pause percentage, silence duration, and speech rhythm standard deviation. Linguistic biomarkers representing the length of the narratives and the number of nouns and auxiliaries also provided discrimination between groups. Altogether, in addition to being significant, these biomarkers satisfied the robustness requirements.

The role of the basal ganglia and cerebellum in adaptation to others' speech rate and rhythm: A study of patients with Parkinson's disease and cerebellar degeneration

BACKGROUND

Spoken language is constantly undergoing change: Speakers within and across social and regional groups influence each other's speech, leading to the emergence and drifts of accents in a language. These processes are driven by mutual unintentional imitation of the phonetic details of others' speech in conversational interactions, suggesting that continuous auditory-motor adaptation takes place in interactive language use and plasticity of auditory-motor representations of speech persists across the lifespan. The brain mechanisms underlying this large-scale social-linguistic behavior are still poorly understood.

RESEARCH AIM

To investigate the role of cerebellar and basal ganglia dysfunctions in unintended adaptation to the speech rhythm and articulation rate of a second speaker.

METHODS

Twelve patients with spinocerebellar ataxia type 6 (SCA6), 15 patients with Parkinson's disease (PD), and 27 neurologically healthy controls (CTRL) participated in two interactive speech tasks, i.e., sentence repetition and "turn-taking" (i.e., dyadic interaction with sentences produced by a model speaker). Production of scripted sentences was used as a control task. Two types of sentence rhythm were distinguished, i.e., regular and irregular, and model speech rate was manipulated in 12 steps between 2.9 and 4.0 syllables per second. Acoustic analyses of the participants' utterances were performed to determine the extent to which participants adapted their speech rate and rhythm to the model.

RESULTS

Neurologically healthy speakers showed significant adaptation of rate in all conditions, and of rhythm in the repetition task and partly also the turn-taking task. Patients with PD showed a stronger propensity to adapt than the controls. In contrast, the patients with cerebellar degeneration were largely insensitive to the model speaker's rate and rhythm. Contrary to expectations, sentences with an irregular speech rhythm exerted a stronger adaptive attraction than regular sentences in the two patient groups.

CONCLUSIONS

Cerebellar degeneration inhibits the propensity to covertly adapt to others' speech. Striatal dysfunction in Parkinson's disease spares or even promotes the tendency to accommodate to other speakers' speech rate and rhythm.

Evaluating a Speech-Specific and a Computerized Step-Training-Specific Rhythmic Intervention in Parkinson's Disease: A Cross-Over, Multi-Arms Parallel Study

Background:

Recent studies suggest movements of speech and gait in patients with Parkinson's Disease (PD) are impaired by a common underlying rhythmic dysfunction. If this being the case, motor deficits in speech and gait should equally benefit from rhythmic interventions regardless of whether it is a speech-specific or step-training-specific approach.

Objective:

In this intervention trial, we studied the effects of two rhythmic interventions on speech and gait. These rhythmic intervention programs are similar in terms of intensity and frequency (i.e., 3x per week, 45 min-long sessions for 4 weeks in total), but differ regarding therapeutic approach (rhythmic speech vs. rhythmic balance-mobility training).

Methods:

This study is a cross-over, parallel multi-arms, single blind intervention trial, in which PD patients treated with rhythmic speech-language therapy (rSLT; N = 16), rhythmic balance-mobility training (rBMT; N = 10), or no therapy (NT; N = 18) were compared to healthy controls (HC; N = 17; matched by age, sex, and education: p > 0.82). Velocity and cadence in speech and gait were evaluated at baseline (BL), 4 weeks (4W-T1), and 6 months (6M-T2) and correlated.

Results:

Parameters in speech and gait (i.e., speaking and walking velocity, as well as speech rhythm with gait cadence) were positively correlated across groups (p < 0.01). Statistical analyses involved repeated measures ANOVA across groups and time, as well as independent and one-samples t-tests for within groups analyses. Statistical analyses were amplified using Reliable Change (RC) and Reliable Change Indexes (RCI) to calculate true clinically significant changes due to the treatment on a patient individual level. Rhythmic intervention groups improved across variables and time (total Mean Difference: 3.07 [SD 1.8]; 95% CI 0.2–11.36]) compared to the NT group, whose performance declined significantly at 6 months (p < 0.01). HC outperformed rBMT and NT groups across variables and time (p < 0.001); the rSLT performed similarly to HC at 4 weeks and 6 months in speech rhythm and respiration.

Conclusions:

Speech and gait deficits in PD may share a common mechanism in the underlying cortical circuits. Further, rSLT was more beneficial to dysrhythmic PD patients than rBMT, likely because of the nature of the rhythmic cue.

In Time with the Beat: Entrainment in Patients with Phonological Impairment, Apraxia of Speech, and Parkinson's Disease

In the present study, we investigated if individuals with neurogenic speech sound impairments of three types, Parkinson’s dysarthria, apraxia of speech, and aphasic phonological impairment, accommodate their speech to the natural speech rhythm of an auditory model, and if so, whether the effect is more significant after hearing metrically regular sentences as compared to those with an irregular pattern. This question builds on theories of rhythmic entrainment, assuming that sensorimotor predictions of upcoming events allow humans to synchronize their actions with an external rhythm. To investigate entrainment effects, we conducted a sentence completion task relating participants’ response latencies to the spoken rhythm of the prime heard immediately before. A further research question was if the perceived rhythm interacts with the rhythm of the participants’ own productions, i.e., the trochaic or iambic stress pattern of disyllabic target words. For a control group of healthy speakers, our study revealed evidence for entrainment when trochaic target words were preceded by regularly stressed prime sentences. Persons with Parkinson’s dysarthria showed a pattern similar to that of the healthy individuals. For the patient groups with apraxia of speech and with phonological impairment, considerably longer response latencies with differing patterns were observed. Trochaic target words were initiated with significantly shorter latencies, whereas the metrical regularity of prime sentences had no consistent impact on response latencies and did not interact with the stress pattern of the target words to be produced. The absence of an entrainment in these patients may be explained by the more severe difficulties in initiating speech at all. We discuss the results in terms of clinical implications for diagnostics and therapy in neurogenic speech disorders.

"Ode to confidence": Poetry groups for dysarthria in multiple sclerosis

Purpose: Approximately 40-50% of people with multiple sclerosis (MS) have dysarthria impacting confidence in communication. This study explored how people with MS experienced a novel therapeutic approach combining dysarthria therapy with poetry in a group format.Method: Participants were recruited through MSWA (formerly known as the Multiple Sclerosis Society of Western Australia), a leading service provider for people living with all neurological conditions in Western Australia. They attended eight weekly sessions led by a speech pathologist and a professional poet. The study was co-designed and qualitative, using observational field notes recorded during sessions and semi-structured in-depth interviews with participants after programme completion. The results from an informal, unstandardised rating scale of communication confidence, along with standardised voice and speech measures, were used to facilitate discussion about confidence in the interviews.Result: Nine participants with MS completed the group programme. Analysis of the qualitative data revealed participants' positive views regarding the pairing of speech pathology and poetry. Thematic analysis identified four core themes: living with MS and its "series of griefs"; belonging to a group - "meeting with a purpose"; the power of poetry; and poetry as a medium for speech pathology.Conclusion: Poetry in combination with dysarthria therapy represents a novel, interprofessional approach for improving communication confidence in individuals with MS.

Syllable as a unit of information transfer in linguistic communication: The entropy syllable parsing model

To understand human language-both spoken and signed-the listener or viewer has to parse the continuous external signal into components. The question of what those components are (e.g., phrases, words, sounds, phonemes?) has been a subject of long-standing debate. We re-frame this question to ask: What properties of the incoming visual or auditory signal are indispensable to eliciting language comprehension? In this review, we assess the phenomenon of language parsing from modality-independent viewpoint. We show that the interplay between dynamic changes in the entropy of the signal and between neural entrainment to the signal at syllable level (4-5 Hz range) is causally related to language comprehension in both speech and sign language. This modality-independent Entropy Syllable Parsing model for the linguistic signal offers insight into the mechanisms of language processing, suggesting common neurocomputational bases for syllables in speech and sign language. This article is categorized under: Linguistics > Linguistic Theory Linguistics > Language in Mind and Brain Linguistics > Computational Models of Language Psychology > Language.

Do Patients With Neurogenic Speech Sound Impairments Benefit From Auditory Priming With a Regular Metrical Pattern?

Purpose Earlier investigations based on word and sentence repetition tasks had revealed that the most prevalent metrical pattern in German (the trochee)-unlike the iambic pattern-facilitates articulation in patients with apraxia of speech (AOS; e.g., Aichert, Späth, & Ziegler, 2016), confirming that segmental and prosodic aspects of speech production interact. In this study, we investigated if articulation in apraxic speakers also benefits from auditory priming by speech with a regular rhythm. Furthermore, we asked if the advantage of regular speech rhythm, if present, is confined to impairments at the motor planning stage of speech production (i.e., AOS) or if it also applies to phonological encoding impairments. Method Twelve patients with AOS, 12 aphasic patients with postlexical phonological impairment (PI), and 36 neurologically healthy speakers were examined. A sequential synchronization paradigm based on a sentence completion task was conducted in conditions where we independently varied the metrical regularity of the prime sentence (regular vs. irregular prime sentence) and the metrical regularity of the target word (trochaic vs. iambic). Results Our data confirmed the facilitating effect of regular (trochaic) word stress on speech accuracy in patients with AOS (target effect). This effect could, for the first time, also be demonstrated in individuals with PI. Moreover, the study also revealed an influence of the metrical regularity of speech input in both patient groups (prime effect). Conclusions Patients with AOS and patients with PI exploited rhythmic cues in the speech of a model speaker for the initiation and the segmental realization of words. There seems to be a robust metrical influence on speech at both the phonological and the phonetic planning stages of speech production.

Communication impairment in Parkinson's disease: Impact of motor and cognitive symptoms on speech and language

Communication impairment is common in Parkinson's disease (PD) and may have both motor speech control and cognitive-linguistic underpinnings. The neurobiology of communication impairment in PD is poorly understood, and work is needed to disentangle the relative contributions of motor and cognitive dysfunction. In clinical practice, cognitive-linguistic impairments are often overlooked despite the large body of research on this topic in neurocognitive and linguistics literature. In this review, we will discuss the roles of motor speech changes, cognitive and linguistic impairment, and other related functions in the communication disabilities of individuals with PD. We will describe the various types of communication difficulties in PD and tools for measuring these symptoms. We will discuss specific deficits that may further understanding of the neurobiology of communication impairment in PD, including voice and speech acoustic changes, linguistic processing and production difficulties, and pausing. We will emphasize the importance of an interdisciplinary approach and the patient perspective on daily communication in guiding future research.

Rhythmic performance in hypokinetic dysarthria: Relationship between reading, spontaneous speech and diadochokinetic tasks

•We investigated speech rhythm in people with Parkinson’s Disease (PwPD) and controls. •Even mildly affected PwPD differed from controls in their rhythmic performance. •PwPD showed less difference between reading and spontaneous speech. •Spontaneous speech highlighted more differences between speakers than reading. •DDK performance did not relate to rhythmic behaviour in connected speech.