TY -的盟Wang Chi-Te盟——汉Ji-Yan盟方,Shih-Hau AU -赖,Ying-Hui PY - 2020 DA - 2020/12/3 TI -动态发声监测与无线麦克风基于语音能源信封:算法开发和验证乔- JMIR Mhealth Uhealth SP - e16746六世- 8 - 12 KW -语音障碍KW -演讲信封KW -发声习惯KW -背景噪音KW -降噪KW -自适应阈值KW -剂量测定法KW - phonotrauma AB -背景:语音障碍主要是由于长期过度使用或滥用造成的，特别是在教师等职业语音使用者中。以前的研究提出了一种连接在前颈部的接触式麦克风，用于动态语音监测;然而，与胶带和电线相关的不便，以及缺乏实时处理，限制了其临床应用。目的:本研究旨在(1)提出一种基于无线麦克风的语音自动检测系统，用于实时监测动态语音;(2)检测受控环境和有噪声条件下的检测精度;(3)报告实际场景下的声速比结果。方法:设计了一种基于能量包络的自适应阈值函数来检测语音的存在。我们邀请了10位教师参与这项研究，并测试了所提出的自动语音检测系统的检测精度和声速比。此外，我们研究了无监督降噪算法(即log最小均方误差)是否能克服所提系统中环境噪声的影响。结果:该系统的语音检测平均准确率为89.9%，范围为81.0%(67,357/83,157帧)至95.0%(199,201/209,685帧)。随后的分析显示，在40-60分钟的教学过程中，语音比率在44.0%(33,019/75,044帧)和78.0%(68,785/88,186帧)之间; 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. SN - 2291-5222 UR - https://mhealth.www.mybigtv.com/2020/12/e16746 UR - https://doi.org/10.2196/16746 UR - http://www.ncbi.nlm.nih.gov/pubmed/33270033 DO - 10.2196/16746 ID - info:doi/10.2196/16746 ER -