AIMC Topic: Dysarthria

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Representation Learning Based Speech Assistive System for Persons With Dysarthria.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Dec 13, 2016
An assistive system for persons with vocal impairment due to dysarthria converts dysarthric speech to normal speech or text. Because of the articulatory deficits, dysarthric speech recognition needs a robust learning technique. Representation learnin...
Treatment Outcome Pattern Recognition, Automated Speech Intelligibility Dysarthria Reproducibility of Results Sensitivity and Specificity Algorithms Speech Production Measurement Communication Devices for People with Disabilities Humans Machine Learning
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Dysarthria Detection with Deep Representation Learning for Patients with Parkinson's Disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Dysarthria is a very common motor speech symptom in Parkinson's disease impairing normal communications of patients. Detection of dysarthria could assist clinical diagnosis and intervention of Parkinson's disease, provide monitoring approach for trea...
Aged Humans Male Female Middle Aged Parkinson Disease Deep Learning Dysarthria
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Dysarthria detection based on a deep learning model with a clinically-interpretable layer.

JASA express letters Jan 1, 2023
Studies have shown deep neural networks (DNN) as a potential tool for classifying dysarthric speakers and controls. However, representations used to train DNNs are largely not clinically interpretable, which limits clinical value. Here, a model with ...
Neural Networks, Computer Deep Learning Dysarthria Humans
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Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria.

The New England journal of medicine Jul 15, 2021
BACKGROUND: Technology to restore the ability to communicate in paralyzed persons who cannot speak has the potential to improve autonomy and quality of life. An approach that decodes words and sentences directly from the cerebral cortical activity of...
Brain-Computer Interfaces Electrocorticography Natural Language Processing Quadriplegia Brain Stem Infarctions Dysarthria Electrodes, Implanted Adult Deep Learning Sensorimotor Cortex Humans Neural Prostheses Male Speech
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A joint-feature learning-based voice conversion system for dysarthric user based on deep learning technology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Dysarthria speakers suffer from poor communication, and voice conversion (VC) technology is a potential approach for improving their speech quality. This study presents a joint feature learning approach to improve a sub-band deep neural network-based...
Speech Production Measurement Dysarthria Deep Learning Speech Intelligibility Voice Self-Help Devices Humans
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Multiple ANN Recognizers for Adaptive Recognition of the Speech of Dysarthric Patients in AAL Systems.

Studies in health technology and informatics Jan 1, 2015
People suffering from neuromuscular disorders are one of the main target groups of speech-controlled Ambient Assisted Living systems. However, the speech of these patients is often distorted because of the dysarthric symptoms of the disease. The dysa...
Equipment Design Speech Intelligibility Amyotrophic Lateral Sclerosis Self-Help Devices Multiple Sclerosis Equipment Failure Analysis Speech Recognition Software Neural Networks, Computer Dysarthria Humans Algorithms Neuromuscular Diseases
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