CI-New: An Open Speech Data Repository for Medical Prediction and Assessment of Neurological Disorders

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This community research-infrastructure project will establish a repository of speech data and voice-processing algorithms to support research aimed at detecting neurological disorders by analyzing speech. Existing techniques to detect neurological disorders are costly or difficult to use in primary medical services. However, neurological disorders often leave a fingerprint in voice and speech production, suggesting that speech signal analysis could provide clinical information to predict certain diseases, diagnose illnesses and assess disease progression or the effectiveness of treatment regimens. Voice-based assessment would have significant advantages including low cost, minimal intrusiveness and ease-of-use. Supporting research aimed at better understanding the link between neurological conditions and speech production to enable new diagnostic tools can have immense benefits. For example, understanding the changes in speech and voice caused by diseases such as Parkinson's disease, cerebellar demyelination and stroke, may provide information for early detection of onset, progression and severity of these diseases. However, such diagnostic tools are still out of reach because of three closely related problems: (1) the lack of an in-depth understanding of the relationship between neurological disorders and phonation and (2) the small and incomplete sets of voice samples used in existing studies, and (3) the lack of voice capture, processing, and analysis tools and algorithms that enable neurological assessment. This project will provide infrastructure to address the final two problems in order to enable research to address the first.The project includes (1) design, rollout, and management of a repository of voice samples; (2) collection of a large number voice samples and medical data from subjects across all parts of the population using a mobile- and web-based crowdsourcing approach, and (3) design, implementation, evaluation and distribution of a set of analytical tools that will provide a unified approach to how speech is analyzed and interpreted. The resulting collection will be a major advance over existing studies that are based on only a few subjects or that do not include subjects from a variety of ages, genders or co-morbidities. The repository and accompanying processing tools will enable research in the area of phonation on the impact of neurological conditions on speech, leading to improved diagnostic and assessment tools. The PIs will also rely on the proposed work for extending their outreach and educational efforts, including mentorship of minority and high-school students, supervision of undergraduate researchers, and the design of current courses based on the proposed repository.