6 citations · 8 across the 5 of their papers we have counts for
6 papers
Investigating the Effects of Diffusion-based Conditional Generative Speech Models Used for Speech Enhancement on Dysarthric Speech
Joanna Reszka, Parvaneh Janbakhshi, Tilak Purohit +1
In this study, we aim to explore the effect of pre-trained conditional generative speech models for the first time on dysarthric speech due to Parkinson's disease recorded in an id…
BraSyn 2023 challenge: Missing MRI synthesis and the effect of different learning objectives
Ivo M. Baltruschat, Parvaneh Janbakhshi, Matthias Lenga
This work addresses the Brain Magnetic Resonance Image Synthesis for Tumor Segmentation (BraSyn) challenge, which was hosted as part of the Brain Tumor Segmentation (BraTS) challen…
Uncertainty Estimation in Contrast-Enhanced MR Image Translation with Multi-Axis Fusion
Ivo M. Baltruschat, Parvaneh Janbakhshi, Melanie Dohmen +1
In recent years, deep learning has been applied to a wide range of medical imaging and image processing tasks. In this work, we focus on the estimation of epistemic uncertainty for…
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…
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…
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…