Vocal Biomarkers
What are vocal biomarkers and why do they matter?
Biomarkers are objective indicators that can be measured from a patient and utilised for the development of medical screening and diagnostic procedures.
Speech is a rich source of such information about an individual’s overall health and wellbeing. However, there are many factors (such as language, recording environment and variability between individuals) which make discerning health status from speech directly a complex process.
This is where our research comes in. Our team of experts are working with speech science, AI and large datasets of medically characterised voices to develop clinically meaningful vocal biomarkers as a means of providing better detection and monitoring for neurological conditions.
If you have any questions regarding our research or opportunities with the team, please get in touch with us at [email protected].
Our Research
Bowden, M., Beswick, E., Tam, J., Perry, D., Smith, A., Newton, J., Chandran, S., Watts, O., & Pal, S. (2023). A systematic review and narrative analysis of digital speech biomarkers in Motor Neuron Disease. npj Digital Medicine, 6, Article 228. doi.org/10.1038/s41746-023-00959-9
Tam, J., Weaver, C., Ihenacho, A., Newton, J., Virgo, B., Barrett, S., Neale, J., Perry, D., Smith, A., Chandran, S., Watts, O., Pal, S., & DASH Consortium. (2025). Digital App for Speech and Health Monitoring Study (DASH): Protocol for a prospective longitudinal case–control observational study for developing speech datasets in neurodegenerative disorders and dementia. BMJ Open, 15(12), e100222. bmjopen.bmj.com/content/15/12/e100222
Tam, J., Weaver, C., Watts, O., Chandran, S., Pal, S., & Rowling Speech Consortium. (2025). Anne Rowling Neurological Speech Corpus: Clinically annotated longitudinal dataset for developing speech biomarkers in neurodegenerative disorders. In Proc. Interspeech 2025 (pp. 5693–5697). doi.org/10.21437/Interspeech.2025-2000
Webber, J. J., Watts, O., Wihlborg, L., Tam, J., Weaver, C., Pal, S., Chandran, S., & Valentini-Botinhao, C. (2026). Comparator loss: An ordinal contrastive loss to derive a severity score for speech-based health monitoring. In Proc. Odyssey 2026 (pp. 136–143). doi.org/10.21437/Odyssey.2026-20
Wihlborg, L., Goodall, J., Wheatley, D., Webber, J. J., Tam, J., Weaver, C., Pal, S., Chandran, S., Seth, S., Watts, O., & Valentini-Botinhao, C. (2026). Evaluating pretrained speech embedding systems for dysarthria detection across heterogenous datasets. In ICASSP 2026 – 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain (pp. 14952–14956). doi.org/10.1109/…