Publications associées à Dysarthrie

On matching data and model in LF-MMI-based dysarthric speech recognition

In light of steady progress in machine learning, automatic speech recognition (ASR) is entering more and more areas of our daily life, but people with dysarthria and other speech pathologies are left behind. Their voices are underrepresented in the trainin ...

EPFL2023

Subspace-Based Learning for Automatic Dysarthric Speech Detection

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

To assist the clinical diagnosis and treatment of speech dysarthria, automatic dysarthric speech detection techniques providing reliable and cost-effective assessment are indispensable. Based on clinical evidence on spectro-temporal distortions associated ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

On Modeling Glottal Source Information for Phonation Assessment in Parkinson's Disease

Mathew Magimai Doss, Julian David Fritsch

Parkinson's disease produces several motor symptoms, including different speech impairments that are known as hypokinetic dysarthria. Symptoms associated to dysarthria affect different dimensions of speech such as phonation, articulation, prosody, and inte ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Automatic Dysarthric Speech Detection Exploiting Pairwise Distance-Based Convolutional Neural Networks

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on analy ...

IEEE2021

Multifocal stimulation of the cerebro-cerebellar loop during the acquisition of a novel motor skill

Friedhelm Christoph Hummel, Takuya Morishita, Elena Beanato, Maximilian Jonas Wessel, Chang-Hyun Park, Philipp Johannes Koch

Transcranial direct current stimulation (tDCS)-based interventions for augmenting motor learning are gaining interest in systems neuroscience and clinical research. Current approaches focus largely on monofocal motorcortical stimulation. Innovative stimula ...

2021

AUTOMATIC DYSARTHRIC SPEECH DETECTION EXPLOITING PAIRWISE DISTANCE-BASED CONVOLUTIONAL NEURAL NETWORKS

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on analy ...

Idiap2020

Dysarthric Speech Recognition with Lattice-Free MMI

Enno Hermann

Recognising dysarthric speech is a challenging problem as it differs in many aspects from typical speech, such as speaking rate and pronunciation. In the literature the focus so far has largely been on handling these variabilities in the framework of HMM/G ...

2020

Soft multimodal neural interfaces for unravelling sensory neurological circuits

Frédéric Pierre Gérald Michoud

Diseases or injuries affecting the nervous system can dramatically disrupt the quality of life. Despite extensive efforts towards treating dysfunctional nervous systems, the pharmacological and electrical approaches generally involved lack the temporal and ...

EPFL2019

PATHOLOGICAL SPEECH INTELLIGIBILITY ASSESSMENT BASED ON THE SHORT-TIME OBJECTIVE INTELLIGIBILITY MEASURE

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Impaired speech intelligibility in motor speech disorders arising due to neurological diseases negatively affects the communication ability and quality of life of patients. Reliable and cost-effective measures to automatically assess speec ...

2019

Pathological Speech Intelligibility Assessment based on the Short-Time Objective Intelligibility Measure

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Impaired speech intelligibility in motor speech disorders arising due to neurological diseases negatively affects the communication ability and quality of life of patients. Reliable and cost-effective measures to automatically assess speech intelligibility ...

IEEE2019

Dysarthrie

On matching data and model in LF-MMI-based dysarthric speech recognition

Subspace-Based Learning for Automatic Dysarthric Speech Detection

On Modeling Glottal Source Information for Phonation Assessment in Parkinson's Disease

Automatic Dysarthric Speech Detection Exploiting Pairwise Distance-Based Convolutional Neural Networks

Multifocal stimulation of the cerebro-cerebellar loop during the acquisition of a novel motor skill

AUTOMATIC DYSARTHRIC SPEECH DETECTION EXPLOITING PAIRWISE DISTANCE-BASED CONVOLUTIONAL NEURAL NETWORKS

Dysarthric Speech Recognition with Lattice-Free MMI

Soft multimodal neural interfaces for unravelling sensory neurological circuits

PATHOLOGICAL SPEECH INTELLIGIBILITY ASSESSMENT BASED ON THE SHORT-TIME OBJECTIVE INTELLIGIBILITY MEASURE

Pathological Speech Intelligibility Assessment based on the Short-Time Objective Intelligibility Measure

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PATHOLOGICAL SPEECH INTELLIGIBILITY ASSESSMENT BASED ON THE SHORT-TIME OBJECTIVE INTELLIGIBILITY MEASURE

Automatic Dysarthric Speech Detection Exploiting Pairwise Distance-Based Convolutional Neural Networks

Dysarthric Speech Recognition with Lattice-Free MMI

Subspace-Based Learning for Automatic Dysarthric Speech Detection

On Modeling Glottal Source Information for Phonation Assessment in Parkinson's Disease

Multifocal stimulation of the cerebro-cerebellar loop during the acquisition of a novel motor skill

Soft multimodal neural interfaces for unravelling sensory neurological circuits

Pathological Speech Intelligibility Assessment based on the Short-Time Objective Intelligibility Measure

AUTOMATIC DYSARTHRIC SPEECH DETECTION EXPLOITING PAIRWISE DISTANCE-BASED CONVOLUTIONAL NEURAL NETWORKS

On matching data and model in LF-MMI-based dysarthric speech recognition