TORONTO, September 24, 2020
At this year’s virtual edition of the International Society for CNS Clinical Trials and Methodology (ISCTM) autumn conference, Winterlight presented a poster outlining methodology for large scale collection of speech data via online marketplaces.
Speech assessments, which are low-burden, non-invasive and can be conducted remotely, can help to characterize subtypes of depression and assist with therapeutic development. In order to do so, large, normative datasets are needed to evaluate the relationship between depression symptoms and speech. This work presents the feasibility of collecting such datasets, quality control procedures for processing speech data from online marketplaces, and exploratory analyses relating depression symptoms to speech characteristics.
Winterlight Labs is commercializing a proprietary language-based diagnostic system that analyzes natural speech to detect and monitor dementia, Alzheimer’s, aphasia, and various other cognitive conditions. Winterlight's scalable platform uses short recorded speech samples to analyze hundreds of linguistic cues, and can detect dementia and other conditions with a high level of accuracy. This is a major improvement over current pencil-and-paper tests which are time-consuming, costly, and difficult to administer. The platform has applications in drug trials, long-term and primary care, and speech-language pathology.
Since its founding, Winterlight Labs has seen strong interest from pharmaceutical companies and other potential partners who view the technology as a major improvement over current methods of detection or screening. The company has gained support from the pan-Canadian AGE-WELL Network of Centres of Excellence (NCE), the Ontario Brain Institute, Ontario Centres of Excellence, and the University of Toronto Banting and Best Centre for Innovation and Entrepreneurship. For more information, visit www.winterlightlabs.com.
Liam Kaufman, CEO
liam [at] winterlightlabs.com