3 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
Reexamining Racial Disparities in Automatic Speech Recognition Performance: The Role of Confounding by Provenance
Changye Li, Trevor Cohen, Serguei Pakhomov
Automatic speech recognition (ASR) models trained on large amounts of audio data are now widely used to convert speech to written text in a variety of applications from video capti…
Too Big to Fail: Larger Language Models are Disproportionately Resilient to Induction of Dementia-Related Linguistic Anomalies
Changye Li, Zhecheng Sheng, Trevor Cohen +1
As artificial neural networks grow in complexity, understanding their inner workings becomes increasingly challenging, which is particularly important in healthcare applications. T…
Useful Blunders: Can Automated Speech Recognition Errors Improve Downstream Dementia Classification?
Changye Li, Weizhe Xu, Trevor Cohen +1
\textbf{Objectives}: We aimed to investigate how errors from automatic speech recognition (ASR) systems affect dementia classification accuracy, specifically in the ``Cookie Theft'…
TRESTLE: Toolkit for Reproducible Execution of Speech, Text and Language Experiments
Changye Li, Weizhe Xu, Trevor Cohen +2
The evidence is growing that machine and deep learning methods can learn the subtle differences between the language produced by people with various forms of cognitive impairment s…