Tootfinder

Evaluating pretrained speech embedding systems for dysarthria detection across heterogenous datasets
Lovisa Wihlborg, Jemima Goodall, David Wheatley, Jacob J. Webber, Johnny Tam, Christine Weaver, Suvankar Pal, Siddharthan Chandran, Sohan Seth, Oliver Watts, Cassia Valentini-Botinhao
https://arxiv.org/abs/2509.19946

Evaluating pretrained speech embedding systems for dysarthria detection across heterogenous datasets
We present a comprehensive evaluation of pretrained speech embedding systems for the detection of dysarthric speech using existing accessible data. Dysarthric speech datasets are often small and can suffer from recording biases as well as data imbalance. To address these we selected a range of datasets covering related conditions and adopt the use of several cross-validations runs to estimate the chance level. To certify that results are above chance, we compare the distribution of scores acros…

Comparator Loss: An Ordinal Contrastive Loss to Derive a Severity Score for Speech-based Health Monitoring
Jacob J Webber, Oliver Watts, Lovisa Wihlborg, David Wheatley, Johnny Tam, Christine Weaver, Suvankar Pal, Siddharthan Chandran, Cassia Valentini-Botinhao
https://arxiv.org/abs/2509.17661

Comparator Loss: An Ordinal Contrastive Loss to Derive a Severity Score for Speech-based Health Monitoring
Monitoring the progression of neurodegenerative disease has important applications in the planning of treatment and the evaluation of future medications. Whereas much of the state-of-the-art in health monitoring from speech has been focused on classifying patients versus healthy controls, or predicting real-world health metrics, we propose here a novel measure of disease progression: the severity score. This score is derived from a model trained to minimize what we call the comparator loss. The…