3 citations · 3 across the 2 of their papers we have counts for
3 papers
DECK: Behavioral Tests to Improve Interpretability and Generalizability of BERT Models Detecting Depression from Text
Jekaterina Novikova, Ksenia Shkaruta
Models that accurately detect depression from text are important tools for addressing the post-pandemic mental health crisis. BERT-based classifiers' promising performance and the…
Lexical Features Are More Vulnerable, Syntactic Features Have More Predictive Power
Jekaterina Novikova, Aparna Balagopalan, Ksenia Shkaruta +1
Understanding the vulnerability of linguistic features extracted from noisy text is important for both developing better health text classification models and for interpreting vuln…
Impact of ASR on Alzheimer's Disease Detection: All Errors are Equal, but Deletions are More Equal than Others
Aparna Balagopalan, Ksenia Shkaruta, Jekaterina Novikova
Automatic Speech Recognition (ASR) is a critical component of any fully-automated speech-based dementia detection model. However, despite years of speech recognition research, litt…