RAPID: Human Sound Localization and Analytics

RAPID：人类声音定位和分析

• 批准号: 2032125
• 负责人: Lili Qiu
• 金额: $ 10万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2032125&HistoricalAwards=false
• 关键词: RAPID; Human; Sound; Localization; Analytics

COVID-19 is spreading at an unprecedented rate resulting in the death of so many people all over the world. Social distancing is so far the most effective method to limit its spread. However, manually enforcing social distancing is not only labor-intensive but also error-prone and even dangerous due to possible physical contact. This project proposes to develop techniques and mobile systems that localize human sound such as cough and voice and alarm a user when someone is within the social distance. If successful, this work will significantly advance the state-of-the-art in wireless sensing and localization. To maximize the impact, the researchers will collaborate with industry and local community and release software to the public. The research outcome will also be incorporated into the graduate and undergraduate curriculum. The proposed research aims to develop algorithms and systems to localize uncontrolled and unknown human sound. A unique advantage is that it does not require cooperation from other phones and whoever uses it can immediately benefit from it. It exploits the phone mobility as the user moves to enable localization. The multi-resolution analysis will be performed on low-frequency voice signals to further enhance accuracy. When another phone is cooperating, it will further leverage the time of flight between the two phones to improve the performance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

COVID-19正在以前所未有的速度蔓延，导致世界各地如此多的人死亡。到目前为止，保持社交距离是限制其传播的最有效方法。然而，手动执行社交距离不仅是劳动密集型的，而且容易出错，甚至由于可能发生身体接触而危险。该项目建议开发技术和移动系统，以定位咳嗽和声音等人类声音，并在有人在社交距离内时向用户发出警报。如果成功，这项工作将显著推进无线传感和定位技术的发展。为了使影响最大化，研究人员将与工业界和当地社区合作，并向公众发布软件。研究成果也将纳入研究生和本科课程。提出的研究旨在开发算法和系统来定位不受控制和未知的人类声音。一个独特的优势是，它不需要其他手机的配合，使用它的人可以立即从中受益。它利用用户移动时的手机移动性来实现本地化。我们会对低频话音信号进行多分辨率分析，以进一步提高准确度。当另一部手机合作时，它会进一步利用两部手机之间的飞行时间来提高性能。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

MAVL: Multiresolution Analysis of Voice Localization

• 发表时间: 2021