565 citations · 953 across the 21 of their papers we have counts for
32 papers
Factors Affecting the Performance of Automated Speaker Verification in Alzheimer's Disease Clinical Trials
Malikeh Ehghaghi, Marija Stanojevic, Ali Akram +1
Detecting duplicate patient participation in clinical trials is a major challenge because repeated patients can undermine the credibility and accuracy of the trial's findings and r…
DEPAC: a Corpus for Depression and Anxiety Detection from Speech
Mashrura Tasnim, Malikeh Ehghaghi, Brian Diep +1
Mental distress like depression and anxiety contribute to the largest proportion of the global burden of diseases. Automated diagnosis systems of such disorders, empowered by recen…
Cost-effective Models for Detecting Depression from Speech
Mashrura Tasnim, Jekaterina Novikova
Depression is the most common psychological disorder and is considered as a leading cause of disability and suicide worldwide. An automated system capable of detecting signs of dep…
Multi-modal deep learning system for depression and anxiety detection
Brian Diep, Marija Stanojevic, Jekaterina Novikova
Traditional screening practices for anxiety and depression pose an impediment to monitoring and treating these conditions effectively. However, recent advances in NLP and speech mo…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Data-driven Approach to Differentiating between Depression and Dementia from Noisy Speech and Language Data
Malikeh Ehghaghi, Frank Rudzicz, Jekaterina Novikova
A significant number of studies apply acoustic and linguistic characteristics of human speech as prominent markers of dementia and depression. However, studies on discriminating de…