Characterizing intonation deficit in motor speech disorders : an autosegmental-metrical analysis of spontaneous speech in hypokinetic dysarthria, ataxic dysarthria and foreign accent syndrome

The autosegmental-metrical (AM) framework represents an established methodology for intonational analysis in unimpaired speaker populations but has found little application in describing intonation in motor speech disorders (MSDs). This study compared the intonation patterns of unimpaired participants (CON) and those with Parkinson's disease (PD), ataxic dysarthria (AT), and foreign accent syndrome (FAS) to evaluate the approach's potential for distinguishing types of MSDs from each other and from unimpaired speech. Spontaneous speech from 8 PD, 8 AT, 4 FAS, and 10 CON speakers were analyzed in relation to inventory and prevalence of pitch patterns, accentuation, and phrasing. Acoustic-phonetic baseline measures (maximum-phonation-duration, speech rate, and F0-variability) were also performed. Results: The analyses yielded differences between MSD and CON groups and between the clinical groups in regard to prevalence, accentuation, and phrasing. AT and FAS speakers used more rising and high pitch accents than PD and CON speakers. The AT group used the highest number of pitch accents per phrase, and all 3 MSD groups produced significantly shorter phrases than the CON group. The study succeeded in differentiating MSDs on the basis of intonational performances by using the AM approach, thus, demonstrating its potential for charting intonational profiles in clinical populations

Relationships between cognitive status, speech impairment and communicative participation in Parkinson’s disease

Aim: To assess the relationships between cognitive status, speech impairment and communicative participation in Parkinson’s disease. Introduction: Speech and communication difficulties, as well as cognitive impairment, are prevalent in Parkinson’s. The contributions of cognitive impairment and acoustic speech characteristics remain equivocal. Relationships between Impairment and Participation levels of the International Classification of Functioning, Disability and Health (ICF) have not been thoroughly investigated. Methods: 45 people with Parkinson’s and 29 familiar controls performed read, mood and conversational speech tasks as part of a multimethod investigation. Data analysis formed three main parts. Depression, cognition and communication were assessed using questionnaires. Phonetic analysis was used to produce an acoustic characterisation of speech. Listener assessment was used to assess conveyance of emotion and intelligibility. Qualitative Content Analysis was used to provide a participant’s insight into speech and communicative difficulties associated with Parkinson’s disease. Results: Cognitive status was significantly associated with certain read speech acoustic characteristics, emotional conveyance and communicative participation. No association was found with intelligibility or conversational speech acoustic characteristics. The only acoustic speech characteristics that predicted intelligibility were intensity and pause in the read speech condition. The contribution of intelligibility to communicative participation was modest. People with Parkinson’s disease reported a range of psychosocial, cognitive and physical factors affecting their speech and communication. Conclusions: I provide evidence for a role for cognitive status in emotional conveyance and communicative participation, but not necessarily general speech production, in Parkinson’s disease. I demonstrate that there may not be a strong relationship between ICF Impairment level speech measures and functional measures of communication. I also highlight the distinction between measures of communication at the ICF Activity and Participation levels. This study demonstrates that reduced participation in everyday communication in Parkinson’s disease appears to result from a complex interplay of physical, cognitive and psychosocial factors. Further research is required to apply these findings to contribute to future advances in speech and language therapy for Parkinson’s disease

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

Purpose: This study aimed to investigate whether rhythm metrics are sensitive to change in speakers with mild hypokinetic dysarthria, whether such changes can be detected in reading and spontaneous speech, and whether diadochokinetic (DDK) performance relates to rhythmic properties of speech tasks. Method: Ten people with Parkinson’s Disease (PwPD) with mild hypokinetic dysarthria and ten healthy control speakers produced DDK repetitions, a reading passage and a spontaneous monologue. Articulation rate, as well as ten rhythm metrics were applied to the speech data. DDK performance was captured by mean, standard deviation (SD) and coefficient of variation (CoV) of syllable duration. Results: Group differences were apparent across both speech tasks, but mainly in spontaneous speech. The control speakers changed their rhythm performance between the two tasks, whereas the PwPD displayed a more constant behaviour. The correlation analysis of speech and DDK tasks resulted in few meaningful relationships. Conclusions: Rhythm metrics appeared to be sensitive to mild levels of impairment in PwPD. They are thus suitable for use as diagnostic or outcome measures. In addition, we demonstrated that conversational data can be used in the investigation of rhythm. Finally, the value of DDK tasks in predicting the rhythm performance during speech could not be demonstrated successfully

Acoustic Changes during Passage Reading in Speakers with Parkinson\u27s Disease

Purpose: The purpose of this study was to evaluate speech changes in Parkinson’s disease (PD) while reading a passage, using both local (i.e., segment level) and global (i.e., utterance level) acoustic measures. Methods: 20 speakers participated in the study (10 PD, 10 neurologically healthy controls). The speakers were asked to read The Caterpillar passage in a conversational mode. A total of five acoustic measures were included (local: vowel duration, Euclidean distance between corner vowels and schwa; global: articulation rate, F0/intensity range). These acoustic measures were compared between two sentences located in the two positions within the paragraph, initial and final. Results: The findings indicated (1) overall speech differences between the two groups such as increased vowel duration and reduced vowel contrast and (2) speech differences between the beginning and end of the passage such as increased articulation rate toward the end. In addition, the results revealed that unlike control speakers, speakers with PD did not show a greater F0 and intensity range in the end compared to the beginning of the passage, which points a limited capability of prosody modulations in PD and its apparent pattern toward the end of passage reading. Discussion: Findings of this study support the notion that within- or across-task acoustic variation should be considered in speech sampling in clinical practice and research

운율 정보를 이용한 마비말장애 음성 자동 검출 및 평가

학위논문 (석사) -- 서울대학교 대학원 : 인문대학 언어학과, 2020. 8. Minhwa Chung.말장애는 신경계 또는 퇴행성 질환에서 가장 빨리 나타나는 증 상 중 하나이다. 마비말장애는 파킨슨병, 뇌성 마비, 근위축성 측삭 경화증, 다발성 경화증 환자 등 다양한 환자군에서 나타난다. 마비말장애는 조음기관 신경의 손상으로 부정확한 조음을 주요 특징으로 가지고, 운율에도 영향을 미치는 것으로 보고된다. 선행 연구에서는 운율 기반 측정치를 비장애 발화와 마비말장애 발화를 구별하는 것에 사용했다. 임상 현장에서는 마비말장애에 대한 운율 기반 분석이 마비말장애를 진단하거나 장애 양상에 따른 알맞은 치료법을 준비하는 것에 도움이 될 것이다. 따라서 마비말장애가 운율에 영향을 미치는 양상뿐만 아니라 마비말장애의 운율 특징을 긴밀하게 살펴보는 것이 필요하다. 구체 적으로, 운율이 어떤 측면에서 마비말장애에 영향을 받는지, 그리고 운율 애가 장애 정도에 따라 어떻게 다르게 나타나는지에 대한 분석이 필요하다. 본 논문은 음높이, 음질, 말속도, 리듬 등 운율을 다양한 측면에 서 살펴보고, 마비말장애 검출 및 평가에 사용하였다. 추출된 운율 특징들은 몇 가지 특징 선택 알고리즘을 통해 최적화되어 머신러닝 기반 분류기의 입력값으로 사용되었다. 분류기의 성능은 정확도, 정밀도, 재현율, F1-점수로 평가되었다. 또한, 본 논문은 장애 중증도(경도, 중등도, 심도)에 따라 운율 정보 사용의 유용성을 분석하였다. 마지막으로, 장애 발화 수집이 어려운 만큼, 본 연구는 교차 언어 분류기를 사용하였다. 한국어와 영어 장애 발화가 훈련 셋으로 사용되었으며, 테스트셋으로는 각 목표 언어만이 사용되었다. 실험 결과는 다음과 같이 세 가지를 시사한다. 첫째, 운율 정보 를 사용하는 것은 마비말장애 검출 및 평가에 도움이 된다. MFCC 만을 사용했을 때와 비교했을 때, 운율 정보를 함께 사용하는 것이 한국어와 영어 데이터셋 모두에서 도움이 되었다. 둘째, 운율 정보는 평가에 특히 유용하다. 영어의 경우 검출과 평가에서 각각 1.82%와 20.6%의 상대적 정확도 향상을 보였다. 한국어의 경우 검출에서는 향상을 보이지 않았지만, 평가에서는 13.6%의 상대적 향상이 나타났다. 셋째, 교차 언어 분류기는 단일 언어 분류기보다 향상된 결과를 보인다. 실험 결과 교차언어 분류기는 단일 언어 분류기와 비교했을 때 상대적으로 4.12% 높은 정확도를 보였다. 이것은 특정 운율 장애는 범언어적 특징을 가지며, 다른 언어 데이터를 포함시켜 데이터가 부족한 훈련 셋을 보완할 수 있 음을 시사한다.One of the earliest cues for neurological or degenerative disorders are speech impairments. Individuals with Parkinsons Disease, Cerebral Palsy, Amyotrophic lateral Sclerosis, Multiple Sclerosis among others are often diagnosed with dysarthria. Dysarthria is a group of speech disorders mainly affecting the articulatory muscles which eventually leads to severe misarticulation. However, impairments in the suprasegmental domain are also present and previous studies have shown that the prosodic patterns of speakers with dysarthria differ from the prosody of healthy speakers. In a clinical setting, a prosodic-based analysis of dysarthric speech can be helpful for diagnosing the presence of dysarthria. Therefore, there is a need to not only determine how the prosody of speech is affected by dysarthria, but also what aspects of prosody are more affected and how prosodic impairments change by the severity of dysarthria. In the current study, several prosodic features related to pitch, voice quality, rhythm and speech rate are used as features for detecting dysarthria in a given speech signal. A variety of feature selection methods are utilized to determine which set of features are optimal for accurate detection. After selecting an optimal set of prosodic features we use them as input to machine learning-based classifiers and assess the performance using the evaluation metrics: accuracy, precision, recall and F1-score. Furthermore, we examine the usefulness of prosodic measures for assessing different levels of severity (e.g. mild, moderate, severe). Finally, as collecting impaired speech data can be difficult, we also implement cross-language classifiers where both Korean and English data are used for training but only one language used for testing. Results suggest that in comparison to solely using Mel-frequency cepstral coefficients, including prosodic measurements can improve the accuracy of classifiers for both Korean and English datasets. In particular, large improvements were seen when assessing different severity levels. For English a relative accuracy improvement of 1.82% for detection and 20.6% for assessment was seen. The Korean dataset saw no improvements for detection but a relative improvement of 13.6% for assessment. The results from cross-language experiments showed a relative improvement of up to 4.12% in comparison to only using a single language during training. It was found that certain prosodic impairments such as pitch and duration may be language independent. Therefore, when training sets of individual languages are limited, they may be supplemented by including data from other languages.1. Introduction 1 1.1. Dysarthria 1 1.2. Impaired Speech Detection 3 1.3. Research Goals & Outline 6 2. Background Research 8 2.1. Prosodic Impairments 8 2.1.1. English 8 2.1.2. Korean 10 2.2. Machine Learning Approaches 12 3. Database 18 3.1. English-TORGO 20 3.2. Korean-QoLT 21 4. Methods 23 4.1. Prosodic Features 23 4.1.1. Pitch 23 4.1.2. Voice Quality 26 4.1.3. Speech Rate 29 4.1.3. Rhythm 30 4.2. Feature Selection 34 4.3. Classification Models 38 4.3.1. Random Forest 38 4.3.1. Support Vector Machine 40 4.3.1 Feed-Forward Neural Network 42 4.4. Mel-Frequency Cepstral Coefficients 43 5. Experiment 46 5.1. Model Parameters 47 5.2. Training Procedure 48 5.2.1. Dysarthria Detection 48 5.2.2. Severity Assessment 50 5.2.3. Cross-Language 51 6. Results 52 6.1. TORGO 52 6.1.1. Dysarthria Detection 52 6.1.2. Severity Assessment 56 6.2. QoLT 57 6.2.1. Dysarthria Detection 57 6.2.2. Severity Assessment 58 6.1. Cross-Language 59 7. Discussion 62 7.1. Linguistic Implications 62 7.2. Clinical Applications 65 8. Conclusion 67 References 69 Appendix 76 Abstract in Korean 79Maste

Phylogenetic reorganization of the basal ganglia: A necessary, but not the only, bridge over a primate Rubicon of acoustic communication

In this response to commentaries, we revisit the two main arguments of our target article. Based on data drawn from a variety of research areas – vocal behavior in nonhuman primates, speech physiology and pathology, neurobiology of basal ganglia functions, motor skill learning, paleoanthropological concepts – the target article, first, suggests a two-stage model of the evolution of the crucial motor prerequisites of spoken language within the hominin lineage: (1) monosynaptic refinement of the projections of motor cortex to brainstem nuclei steering laryngeal muscles, and (2) subsequent “vocal-laryngeal elaboration” of cortico-basal ganglia circuits, driven by human-specific FOXP2 mutations. Second, as concerns the ontogenetic development of verbal communication, age-dependent interactions between the basal ganglia and their cortical targets are assumed to contribute to the time course of the acquisition of articulate speech. Whereas such a phylogenetic reorganization of cortico-striatal circuits must be considered a necessary prerequisite for ontogenetic speech acquisition, the 30 commentaries – addressing the whole range of data sources referred to – point at several further aspects of acoustic communication which have to be added to or integrated with the presented model. For example, the relationships between vocal tract movement sequencing – the focus of the target article – and rhythmical structures of movement organization, the connections between speech motor control and the central-auditory and central-visual systems, the impact of social factors upon the development of vocal behavior (in nonhuman primates and in our species), and the interactions of ontogenetic speech acquisition – based upon FOXP2-driven structural changes at the level of the basal ganglia – with preceding subvocal stages of acoustic communication as well as higher-order (cognitive) dimensions of phonological development. Most importantly, thus, several promising future research directions unfold from these contributions – accessible to clinical studies and functional imaging in our species as well as experimental investigations in nonhuman primates

How does prosodic deficit impact naïve listeners recognition of emotion? An analysis with speakers affected by Parkinson's disease

Abstract This study aimed to understand the impact of the prosodic deficit in Parkinson's disease (PD) on the communicative effectiveness of vocal expression of emotion. Fourteen patients with PD and 13 healthy control subjects (HC) uttered the phrase "non è possible, non ora" ("It is not possible, not now") six times reading different emotional narrations. Three experts evaluated the PD subjects' vocal production in terms of their communicative effectiveness. The PD patients were divided into two groups: PD+ (with residual effectiveness) and PD− (with impaired effectiveness). The vocal productions were administered to 30 naïve listeners. They were requested to label the emotion they recognized and to make judgments about their communicative effectiveness. The PD speakers were perceived as less effective than the HC speakers in conveying emotions (especially fear and anger). The PD− group was the most impaired in the expression of emotion, suggesting that speech disorders impact differently at the same stage of the disease with varying degrees of severity

Computational Language Assessment in patients with speech, language, and communication impairments

Speech, language, and communication symptoms enable the early detection, diagnosis, treatment planning, and monitoring of neurocognitive disease progression. Nevertheless, traditional manual neurologic assessment, the speech and language evaluation standard, is time-consuming and resource-intensive for clinicians. We argue that Computational Language Assessment (C.L.A.) is an improvement over conventional manual neurological assessment. Using machine learning, natural language processing, and signal processing, C.L.A. provides a neuro-cognitive evaluation of speech, language, and communication in elderly and high-risk individuals for dementia. ii. facilitates the diagnosis, prognosis, and therapy efficacy in at-risk and language-impaired populations; and iii. allows easier extensibility to assess patients from a wide range of languages. Also, C.L.A. employs Artificial Intelligence models to inform theory on the relationship between language symptoms and their neural bases. It significantly advances our ability to optimize the prevention and treatment of elderly individuals with communication disorders, allowing them to age gracefully with social engagement.Comment: 36 pages, 2 figures, to be submite

The Effect of Formant Measurement Methods on Vowel Space in Patients with Parkinson\u27s Disease Before and After Voice Treatment

LSVT-LOUD® has been shown to improve phonatory quality in patients with PD. Previous studies have shown an increase in vowel space area following treatment, but questions remain regarding possible methodological issues in interaction with phonatory factors. This study addresses these questions by comparing multiple formant measurment methods and vowel space metrics. Ten participants were recorded on two separate days before and after treatment. Formants were measured using a human-guided reference (dubbed \u27HGIM\u27), LPC, and two forms of cepstrally-liftered spectrum. Multiple vowel space metrics including the vowel articulation index, F2i/F2u, area of the vowel quadrilateral, and vowel formant dispersion utilized both lax and corner vowels to explore vowel space changes. Analysis revealed no significant change in vowel space following LSVT. High variability in LPC with a fixed coefficient was noted. These results do not support previous claims of increased vowel space but suggest that formant measurement methods may influence results

Role of Therapeutic Devices in Enhancing Speech Intelligibility and Vocal Intensity in an Individual with Parkinson’s Disease

The prevailing speech therapy techniques for treating hypokinetic dysarthria in individuals with Parkinson\u27s disease (PD) yields improvements within the clinical setting, however, maintenance and generalization of acquired behaviors continue to be a challenge. The purpose of this study was to investigate the effects of portable therapeutic devices including Ambulatory Phonation Monitor with biofeedback (APM) and auditory masker in maintenance and carryover of improved speech. Our participant was an individual diagnosed with PD for the past 25 years who continued to display speech disturbances despite undergoing several behavioral speech therapy programs and neurosurgical procedures. Speech intelligibility and average intensity measures under automatic, elicited, and spontaneous speech tasks were recorded pre- and postusage of APM and auditory masker for a period of 1 week each. Preliminary findings showed no significant difference in the measures between means (P\u3e0.05) across all tasks for both the devices. Suggestions for future research on therapeutic devices are discussed