Psychologynpj Digital Medicine
Assessing the accuracy of automatic speech recognition for psychotherapy
A. S. Miner, A. Haque, et al.
This study, conducted by a team of experts including Adam S. Miner and Albert Haque, explores the potential of a HIPAA-compliant automatic speech recognition system to enhance psychotherapy audio transcription. While demonstrating promising results in interpreting depression-related utterances, the system's accuracy reveals further development is needed before it can guarantee individual safety monitoring.
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Medicine and Health
Novel statistical approach for assessing the persistence of the circadian rhythms of social activity from telephone call detail records in older adults
T. Aubourg, J. Demongeot, et al.
Environmental Studies and Forestry
The role of the IPCC in assessing actionable evidence for climate policymaking
H. Pollitt, J. Mercure, et al.
Medicine and Health
An automatic speech analytics program for digital assessment of stress burden and psychosocial health
A. M. Y. Chu, B. S. Y. Lam, et al.
Computer Science
Neural signals, machine learning, and the future of inner speech recognition
A. T. Chowdhury, A. Hassanein, et al.
