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Development and testing of a portable vocal accumulator
Harold A Cheyne1, Helen M Hanson, Ronald P Genereux
1Voice and Speech Laboratory, Massachusetts Eye and Ear Infirmary, Boston 02114, USA. harold_cheyne@meei.harvard.edu
Journal of Speech, Language, and Hearing Research : JSLHR
|January 1, 2004
Summary
This study introduces the Portable Vocal Accumulator (PVA), a device for unobtrusive, long-term voice monitoring. The PVA effectively captures vocal parameters like fundamental frequency and duration for both normal and dysphonic voices.
Area of Science:
- Biomedical Engineering
- Speech Science
- Health Informatics
Background:
- Long-term ambulatory monitoring of voice use is crucial for understanding vocal health and disorders.
- Existing methods may be obtrusive or lack the capacity for continuous data collection.
- Developing unobtrusive technology is key for ecological validity in voice research.
Purpose of the Study:
- To design and test the Portable Vocal Accumulator (PVA) for unobtrusive, long-term ambulatory voice use monitoring.
- To evaluate the PVA's capability in analyzing voice data from individuals with normal and dysphonic voices.
- To explore effective data visualization methods for extensive long-term vocal monitoring.
Main Methods:
- Development of the Portable Vocal Accumulator (PVA) featuring a digital signal processor and neck-placed miniature accelerometer.
- Collection of accelerometer recordings from 99 participants with normal or dysphonic voices.
- Testing of PVA specifications and capabilities using collected voice data.
Main Results:
- The PVA prototype is pocket-sized, lightweight, and capable of sampling 11 hours of voice-use data.
- The device can estimate fundamental frequency, sound pressure level, and phonation duration.
- Accelerometer recordings proved useful for testing PVA specifications and exploring data displays.
Conclusions:
- The Portable Vocal Accumulator (PVA) is a viable tool for unobtrusive, long-term ambulatory monitoring of voice use.
- The PVA demonstrates potential for analyzing vocal characteristics in both healthy and disordered voices.
- Further development can optimize data display for clinical and research applications.