基于YOLO和TDOA的会议中的自动扬声器定位
Chen-Chiung Hsieh1, Men-Ru Lu1, Hsiao-Ting Tseng2
1Department of Computer Science and Engineering, Tatung University, Taipei City 104, Taiwan.
Sensors (Basel, Switzerland)
|July 29, 2023
概括
本研究介绍了一种新的扬声器本地化方法,用于使用YOLO对象检测和到达时间差 (TDOA) 音频本地化进行视频会议. 综合方法实现了高精度,改进了单一来源方法.
科学领域:
- 计算机视觉 计算机视觉
- 声学信号处理 声学信号处理
- 人与计算机的交互
背景情况:
- 视频会议在COVID-19大流行期间变得普遍,突出了标准网络摄像机在跟踪演讲者的局限性.
- 目前的网络摄像头技术缺乏自动翻/倾和扬声器锁定功能,阻碍了动态交互.
- 有效的演讲者识别对于增强虚拟沟通和会议参与度至关重要.
研究的目的:
- 开发一个用于视频会议中实时定位演讲者的自动化系统.
- 整合视觉 (物体检测) 和听觉 (声音源定位) 线索,以精确跟踪扬声器.
- 评估拟议的组合方法与单个技术的性能.
主要方法:
- 利用YOLO (You Only Look Once) 对象检测来识别个人并检测口腔运动 (说话指标).
- 使用到达时间差异 (TDOA) 带有麦克风阵列来确定声音源的角度.
- 结合YOLO衍生空间坐标与TDOA角度,以使用逆三角学准确定位扬声器.
主要成果:
- YOLOX-Tiny实现了85.2%的定位回忆率;仅TDOA的回忆率达到88%.
- 综合的YOLOX-Tiny和TDOA方法的回忆率为86.7%,精度为100%,准确率为94.5%.
- 综合方法表现出优异的性能,而不是使用视觉或听觉定位独立使用.
结论:
- 拟议的方法有效地定位了视频会议设置中的主动演讲者.
- 整合YOLO物体检测和TDOA显著提高了扬声器定位的准确性和可靠性.
- 这项技术为改善虚拟会议中的互动性和用户体验提供了强大的解决方案.
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