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首页> 外文期刊>JMIR mHealth and uHealth >Ambulatory Phonation Monitoring With Wireless Microphones Based on the Speech Energy Envelope: Algorithm Development and Validation
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Ambulatory Phonation Monitoring With Wireless Microphones Based on the Speech Energy Envelope: Algorithm Development and Validation

机译:基于语音能量信封的无线麦克风监控监控:算法开发和验证

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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, (2) examine the detection accuracy under controlled environment and noisy conditions, and (3) report the 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 10 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 (ie, log minimum mean square error) can overcome the influence of environmental noise in the proposed system. Results The proposed system exhibited an average accuracy of speech detection of 89.9%, ranging from 81.0% (67,357/83,157 frames) to 95.0% (199,201/209,685 frames). Subsequent analyses revealed a phonation ratio between 44.0% (33,019/75,044 frames) and 78.0% (68,785/88,186 frames) during teaching sessions of 40-60 minutes; the durations of most of the phonation segments were less than 10 seconds. The presence of background noise reduced the accuracy of the automatic speech detection system, and an adjuvant noise reduction function could effectively improve the accuracy, especially under stable noise conditions. Conclusions This study demonstrated an average detection accuracy of 89.9% 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.
机译:背景语音障碍主要是由慢性过度使用或滥用产生的,特别是在职业语音用户,如教师。以前的研究提出了一个接触麦克风,附着在前颈上用于动态颈部的语音监测;然而,与胶带和布线相关的不便,随着缺乏实时处理,限制了其临床应用。目的本研究旨在(1)提出使用无线麦克风进行实时动态语音监测的自动语音检测系统,(2)检查受控环境下的检测精度和嘈杂的条件,(3)报告发声率的结果在实际情况下。方法设计自适应阈值函数以检测基于能量包络的语音存在。我们邀请了10名教师参与了这项研究,并测试了关于检测精度和发声比的提出的自动语音检测系统的性能。此外,我们调查了无监督的降噪算法(即,日志最小均方误差)是否可以克服所提出的系统中环境噪声的影响。结果拟议的系统表现出言语检测的平均准确性89.9%,范围从81.0%(67,357 / 83,157帧)到95.0%(199,201 / 209,685帧)。随后的分析显示44.0%(33,019 / 75,044帧)和78.0%(68,785 / 88,186帧)的发声比在40-60分钟的教学期间;大多数音量段的持续时间小于10秒。背景噪声的存在降低了自动语音检测系统的准确性,并且佐剂降噪功能可以有效地提高精度,尤其是在稳定的噪声条件下。结论本研究在具有无线麦克风的建议的自动语音检测系统中展示了89.9%的平均检测精度。发声率的初步结果与先前研究的初步结果相当。虽然无线麦克风易受背景噪声的影响,但额外的降噪功能可以缓解这种限制。这些结果表明,所提出的系统可以应用于职业语音用户的动态语音监测。

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