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Developing an acoustic-phonetic characterization of dysarthric speech in French

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TLDR
The requirement of a structured and organized computerized platform in order to store, organize and make accessible (for selected and protected usage) dysarthric speech corpora and associated patients’ clinical information is outlined.
Abstract
This paper presents the rationale, objectives and advances of an on-going project (the DesPho-APaDy project funded by the French National Agency of Research) which aims to provide a systematic and quantified description of French dysarthric speech, over a large population of patients and three dysarthria types (related to the parkinson's disease, the Amyotrophic Lateral Sclerosis disease, and a pure cerebellar alteration). The two French corpora of dysarthric patients, from which the speech data have been selected for analysis purposes, are firstly described. Secondly, this paper discusses and outlines the requirement of a structured and organized computerized platform in order to store, organize and make accessible (for selected and protected usage) dysarthric speech corpora and associated patients' clinical information (mostly disseminated in different locations: labs, hospitals, ...). The design of both a computer database and a multi-field query interface is proposed for the clinical context. Finally, advances of the project related to the selection of the population used for the dysarthria analysis, the preprocessing of the speech files, their orthographic transcription and their automatic alignment are also presented.

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Citations
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Proceedings ArticleDOI

Data Augmentation Using Healthy Speech for Dysarthric Speech Recognition.

TL;DR: Data augmentation using temporal and speed modifications to healthy speech to simulate dysarthric speech is explored using tempo based and speed based data augmentation respec-tively as compared to ASR performance using healthy speech alone for training.
Journal ArticleDOI

How to manage sound, physiological and clinical data of 2500 dysphonic and dysarthric speakers?

TL;DR: A database model designed for the storage and accessibility of various speech disorder data including signals, clinical evaluations and patients' information is proposed and recommended based on MySQL, a relational database management system.
Proceedings ArticleDOI

Automatic Prediction of Speech Evaluation Metrics for Dysarthric Speech

TL;DR: The proposed approach, evaluated on 129 French dysarthric speakers from the DesPhoAPady and VML databases, is proven to be efficient for the modeling of patient's production and capable of detecting the evolution of speech quality.
Journal ArticleDOI

Automatic Detection of Phone-Based Anomalies in Dysarthric Speech

TL;DR: This article investigates automatic speech processing approaches dedicated to the detection and localization of abnormal acoustic phenomena in speech signal produced by people with speech disorders and proposes two different approaches that obtain very encouraging results.
References
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Journal ArticleDOI

Differential Diagnostic Patterns of Dysarthria

TL;DR: Thirty-second speech samples were studied of at least 30 patients in each of 7 discrete neurologic groups, each patient unequivocally diagnosed as being a representative of his diagnostic group, leading to results leading to these conclusions.
Journal ArticleDOI

Clusters of deviant speech dimensions in the dysarthrias.

TL;DR: Correlation matrices were used to demonstrate co-occurrence of deviant speech dimensions observed and led to the emergence of eight distinctive clusters of dysfunction, which may serve as hypotheses for more accurate physiologic and neurophysiologic measurements.
Book

Clinical management of sensorimotor speech disorders

TL;DR: This volume is organized by syndrome, and is divided into the following three sections: nature and differential diagnosis; clinical assessment; clinical management, with a major emphasis on specific treatment techniques.
Journal ArticleDOI

Changes induced by levodopa and subthalamic nucleus stimulation on parkinsonian speech

TL;DR: It seems that motor speech subcomponents can be improved like other limb motor aspect, but that complex coordination of all speech anatomical substrates is not responsive to STN stimulation.
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