Concept

Phonétique articulatoire

Publications associées (28)

Unsupervised Voice Activity Detection by Modeling Source and System Information using Zero Frequency Filtering

Voice activity detection (VAD) is an important pre-processing step for speech technology applications. The task consists of deriving segment boundaries of audio signals which contain voicing information. In recent years, it has been shown that voice source ...

2022

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

Probabilistic Symbol Sequence Matching and its Application to Pathological Speech Intelligibility Assessment

Julian David Fritsch

Matching of a test signal to a reference word hypothesis forms the core of many speech processing problems, including objective speech intelligibility assessment. This paper first shows that the comparison of two speech signals can be formulated as matchin ...

Idiap2021

Utterance Verification-Based Dysarthric Speech Intelligibility Assessment Using Phonetic Posterior Features

Mathew Magimai Doss, Julian David Fritsch

In the literature, the task of dysarthric speech intelligibility assessment has been approached through development of different low-level feature representations, subspace modeling, phone confidence estimation or measurement of automatic speech recognitio ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Novel Methods for Incorporating Prior Knowledge for Automatic Speech Assessment

Subrahmanya Pavankumar Dubagunta

Speech signal conveys several kinds of information such as a message, speaker identity, emotional state of the speaker and social state of the speaker. Automatic speech assessment is a broad area that refers to using automatic methods to predict human judg ...

EPFL2021

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

Idiap2020

HMM-based Approaches to Model Multichannel Information in Sign Language inspired from Articulatory Features-based Speech Processing

Marzieh Razavi, Sandrine Tornay, Necati Cihan Camgöz

Sign language conveys information through multiple channels, such as hand shape, hand movement, and mouthing. Modeling this multi-channel information is a highly challenging problem. In this paper, we elucidate the link between spoken language and sign lan ...

IEEE2019

Triple Contrast CT Method Enables Simultaneous Evaluation of Articular Cartilage Composition and Segmentation

Goran Lovric

Early degenerative changes of articular cartilage are detected using contrast-enhanced computed tomography (CT) with a cationic contrast agent (CA). However, cationic CA diffusion into degenerated cartilage decreases with proteoglycan depletion and increas ...

2019

Learning voice source related information for depression detection

Subrahmanya Pavankumar Dubagunta

During depression neurophysiological changes can occur, which may affect laryngeal control i.e. behaviour of the vocal folds. Characterising these changes in a precise manner from speech signals is a non trivial task, as this typically involves reliable se ...

IEEE2019

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