Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Oct 23, 2019
Date Accepted: Oct 3, 2020
Ambulatory Phonation Monitoring with Wireless Microphones based on Speech Energy Envelope
ABSTRACT
Background:
Voice disorders mainly result from chronic overuse or abuse, particularly in occupational voice users such as teachers. Previous studies proposed a contact microphone attached to the anterior neck for ambulatory voice monitoring; however, the inconvenience associated with taping and wiring, along with the lack of real-time processing, has limited its clinical application.
Objective:
This study aims to (1) propose an automatic speech detection system using wireless microphones for real-time ambulatory voice monitoring, and (2) examine the detection accuracy under controlled environment and noisy conditions, and (3) report the preliminary results of the phonation ratio in practical scenarios.
Methods:
We designed an adaptive threshold function to detect the presence of speech based on the energy envelope. We invited ten teachers to participate in this study and tested the performance of the proposed automatic speech detection system regarding detection accuracy and phonation ratio. Moreover, we investigated whether the unsupervised noise reduction algorithm, i.e., log minimum mean squared error, can overcome the influence of environmental noise in the proposed system.
Results:
The proposed system exhibited an average accuracy of speech detection accuracy ranging as 90 % (range 81–94%).. Subsequent analyses revealed a phonation ratio between 50 and 78% during teaching sessions of 40–60 min; the duration of most of the phonation segments was less than 10 s. Presence of background noise reduced the accuracy of the automatic speech detection system, and adjuvant noise reduction function can effectively improve the accuracy by up to 45.8%, especially under stable noise conditions (e.g., white noise).
Conclusions:
This study demonstrated an average detection accuracy of 90% in the proposed automatic speech detection system with wireless microphones. The preliminary results for the phonation ratio were comparable to those of previous studies. Although the wireless microphones are susceptible to background noise, an additional noise reduction function can alleviate this limitation. These results indicate that the proposed system can be applied for ambulatory voice monitoring in occupational voice users.
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