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This project targets the millions who suffer from voice disorders. It aims to develop new methods for quantifying voice quality disorders, establish relationships among different voice quality dimensions, develop fundamental scales of voice quality, and to develop computational models to predict voice quality perception from a recording.


The proposed project seeks to understand the perception of dysphonic voice quality (VQ) and to develop an innovative approach to quantify VQ through models based on well-established experimental and mathematical approaches, such as those used in psychoacoustics, engineering and computer sciences. The proposed science will advance our knowledge of the cognitive processes underlying VQ perception as well as allow linking VQ perception to underlying acoustics and vocal fold physiology. The practical outcomes include development of metrics that can easily be translated to practice and have a direct impact on clinical care and in other non-clinical applications. The development of a universally accepted standard for voice quality measurement is a grand goal, and the proposed project will bring us significantly closer to this possibility. Supported by two prior NIH grants, this project has made significant advances towards addressing this problem. Our research team is highly multidisciplinary combining knowledge from hearing science, psychoacoustics, speech science, speech-language pathology and computer/electrical engineering


National Institutes of Health

Principal Investigator

Rahul Shrivastav

Active Since

July 2007