activity
20202022
most citedTemporal envelope and fine structure cues for dysarthric speech detection using CNNs

26 citations · 36 across the 7 of their papers we have counts for

collaborators

7 papers

eess.AS2022★ 1 cited

On using the UA-Speech and TORGO databases to validate automatic dysarthric speech classification approaches

Guilherme Schu, Parvaneh Janbakhshi, Ina Kodrasi

Although the UA-Speech and TORGO databases of control and dysarthric speech are invaluable resources made available to the research community with the objective of developing robus…

eess.AS2021★ 2 cited

Experimental investigation on STFT phase representations for deep learning-based dysarthric speech detection

Parvaneh Janbakhshi, Ina Kodrasi

Mainstream deep learning-based dysarthric speech detection approaches typically rely on processing the magnitude spectrum of the short-time Fourier transform of input signals, whil…

eess.AS2021★ 26 cited

Temporal envelope and fine structure cues for dysarthric speech detection using CNNs

Ina Kodrasi

Deep learning-based techniques for automatic dysarthric speech detection have recently attracted interest in the research community. State-of-the-art techniques typically learn neu…

eess.AS2021★ 6 cited

Supervised Speech Representation Learning for Parkinson's Disease Classification

Parvaneh Janbakhshi, Ina Kodrasi

Recently proposed automatic pathological speech classification techniques use unsupervised auto-encoders to obtain a high-level abstract representation of speech. Since these repre…

eess.AS2020

Multi-task single channel speech enhancement using speech presence probability as a secondary task training target

L. Wang, J. Zhu, I. Kodrasi

To cope with reverberation and noise in single channel acoustic scenarios, typical supervised deep neural network~(DNN)-based techniques learn a mapping from reverberant and noisy…

eess.AS2020

Automatic dysarthric speech detection exploiting pairwise distance-based convolutional neural networks

P. Janbakhshi, I. Kodrasi, H. Bourlard

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 p…

cs.SD2020★ 1 cited

Automatic and perceptual discrimination between dysarthria, apraxia of speech, and neurotypical speech

I. Kodrasi, M. Pernon, M. Laganaro +1

Automatic techniques in the context of motor speech disorders (MSDs) are typically two-class techniques aiming to discriminate between dysarthria and neurotypical speech or between…