Vocal markers from sustained phonation in Huntington's Disease

Disease-modifying treatments are currently assessed in neurodegenerative diseases. Huntington's Disease represents a unique opportunity to design automatic sub-clinical markers, even in premanifest gene carriers. We investigated phonatory impairments as potential clinical markers and propose them for both diagnosis and gene carriers follow-up. We used two sets of features: Phonatory features and Modulation Power Spectrum Features. We found that phonation is not sufficient for the identification of sub-clinical disorders of premanifest gene carriers. According to our regression results, Phonatory features are suitable for the predictions of clinical performance in Huntington's Disease.Comment: To appear at INTERSPEECH 2020. 1 pages of supplementary material appear only in the arxiv version. Code to replicate https://github.com/bootphon/sustained-phonation-feature

Modeling Sub-Band Information Through Discrete Wavelet Transform to Improve Intelligibility Assessment of Dysarthric Speech

The speech signal within a sub-band varies at a fine level depending on the type, and level of dysarthria. The Mel-frequency filterbank used in the computation process of cepstral coefficients smoothed out this fine level information in the higher frequency regions due to the larger bandwidth of filters. To capture the sub-band information, in this paper, four-level discrete wavelet transform (DWT) decomposition is firstly performed to decompose the input speech signal into approximation and detail coefficients, respectively, at each level. For a particular input speech signal, five speech signals representing different sub-bands are then reconstructed using inverse DWT (IDWT). The log filterbank energies are computed by analyzing the short-term discrete Fourier transform magnitude spectra of each reconstructed speech using a 30-channel Mel-filterbank. For each analysis frame, the log filterbank energies obtained across all reconstructed speech signals are pooled together, and discrete cosine transform is performed to represent the cepstral feature, here termed as discrete wavelet transform reconstructed (DWTR)- Mel frequency cepstral coefficient (MFCC). The i-vector based dysarthric level assessment system developed on the universal access speech corpus shows that the proposed DTWRMFCC feature outperforms the conventional MFCC and several other cepstral features reported for a similar task. The usages of DWTR- MFCC improve the detection accuracy rate (DAR) of the dysarthric level assessment system in the text and the speaker-independent test case to 60.094 % from 56.646 % MFCC baseline. Further analysis of the confusion matrices shows that confusion among different dysarthric classes is quite different for MFCC and DWTR-MFCC features. Motivated by this observation, a two-stage classification approach employing discriminating power of both kinds of features is proposed to improve the overall performance of the developed dysarthric level assessment system. The two-stage classification scheme further improves the DAR to 65.813 % in the text and speaker- independent test case

Vocal markers from sustained phonation in Huntington's Disease

To appear at INTERSPEECH 2020. 1 pages of supplementary material appear only in the arxiv version. Code to replicate https://github.com/bootphon/sustained-phonation-featuresInternational audienceDisease-modifying treatments are currently assessed in neurodegenerative diseases. Huntington's Disease represents a unique opportunity to design automatic sub-clinical markers, even in premanifest gene carriers. We investigated phonatory impairments as potential clinical markers and propose them for both diagnosis and gene carriers follow-up. We used two sets of features: Phonatory features and Modulation Power Spectrum Features. We found that phonation is not sufficient for the identification of sub-clinical disorders of premanifest gene carriers. According to our regression results, Phonatory features are suitable for the predictions of clinical performance in Huntington's Disease

Emotional processing and communication in people with Huntington's disease:a mixed methods inquiry

Huntington's disease (HD) is a progressive neurodegenerative disorder caused by the inheritance of the mutation of a protein called Huntingtin. Its typical symptoms include motor impairments, cognitive deterioration, and significant psychological difficulties. All these impairments can have a significant effect on the communication of affected individuals, including nonverbal components such as emotional processing. However, the current literature on HD appears to be particularly characterised by a medical approach to the topic, with little evidence from studies adopting a psychological perspective. Thus, the overarching aim of the current thesis was to investigate the impact of Huntington's disease on the emotional processing and communication of affected individuals from a health psychology perspective and with the adoption of a mixed-methods approach. After an initial scoping review of the literature, a qualitative study was conducted in the first phase of the research project, with the aim of exploring the perspectives on communication of people with symptomatic HD. In the second phase, two quantitative investigations were carried out, specifically addressing how HD affects emotional processing - in particular emotion regulation and recognition - in symptomatic and presymptomatic individuals. The results showed that, although emotional processing and communication are affected by HD, the achievement of feelings of control, better emotion regulation, effective medication regimes, and close interpersonal relationships can play a pivotal role in alleviating the burden of the disease. In addition, emotion regulation and emotional body language (EBL) recognition abilities were both impaired in symptomatic individuals, while evidence with presymptomatic people suggested a relative preservation of these skills. In both cases, no significant relationship was found between these abilities. However, the relationship between depressive symptoms and specific elements of emotion regulation such as emotional awareness should be further explored in presymptomatic participants, as it may play a potential precursory role in the development of emotion recognition impairments in fully symptomatic individuals. The implications of the findings for theory and practice are discussed, and possible directions for future research are provided

A comparison study on patient-psychologist voice diarization

International audienceConversations between a clinician and a patient, in natural conditions, are valuable sources of information for medical follow-up. The automatic analysis of these dialogues could help extract new language markers and speed up the clinicians' reports. Yet, it is not clear which model is the most efficient to detect and identify the speaker turns, especially for individuals with speech disorders. Here, we proposed a split of the data that allows conducting a comparative evaluation of different diarization methods. We designed and trained end-to-end neural network architectures to directly tackle this task from the raw signal and evaluate each approach under the same metric. We also studied the effect of fine-tuning models to find the best performance. Experimental results are reported on naturalistic clinical conversations between Psychologists and Interviewees, at different stages of Huntington's disease, displaying a large panel of speech disorders. We found out that our best end-to-end model achieved 19.5% IER on the test set, compared to 23.6% achieved by the finetuning of the X-vector architecture. Finally, we observed that we could extract clinical markers directly from the automatic systems, highlighting the clinical relevance of our methods

Extreme capsule is a bottleneck for ventral pathway

As neuroscience literature suggests, extreme capsule is considered a whiter matter tract. Nevertheless, it is not clear whether extreme capsule itself is an association fiber pathway or only a bottleneck for other association fibers to pass. Via our review, investigating anatomical position, connectivity and cognitive role of the bundles in extreme capsule, and by analyzing data from the dissection, it can be argued that extreme capsule is probably a bottleneck for the passage of uncinated fasciculus (UF) and inferior fronto-occipital fasciculus (IFOF), and these fasciculi are responsible for the respective roles in language processing. © 202