Towards Sensing Acoustic Cyber-Physical Coupling for Novel Mobile Systems
Pages 154 - 155
Abstract
This paper presents recent findings on two novel mobile systems that leverage the acoustic coupling between mobile devices and the physical environment. Firstly, an acoustic sensing system is developed for mobile telecommunication systems, utilizing the reverberation of sound in rooms to detect robocallers. This approach aims to address the prevalent issue of unwanted automated calls. Secondly, the paper explores the concept of bone conduction in speech and introduces a speech enhancement system specifically designed for head-mounted wearables. By leveraging bone conduction technology, VibVoice system is developed to improve the speech quality in noisy environments.
References
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Federal Trade Commission. 2020. Robocalls. https://www.consumer.ftc.gov/features/feature-0025-robocalls.
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Sri Harsha Dumpala and KNRK Raju Alluri. 2017. An algorithm for detection of breath sounds in spontaneous speech with application to speaker recognition. In International conference on speech and computer. Springer.
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Andrea Ferlini, Dong Ma, Robert Harle, and Cecilia Mascolo. 2021. EarGate: Gait-Based User Identification with in-Ear Microphones. In MobiCom.
[4]
Lixing He, Haozheng Hou, Shuyao Shi, Xian Shuai, and Zhenyu Yan. 2023. Towards Bone-Conducted Vibration Speech Enhancement on Head-Mounted Wearables. In MobiSys.
[5]
Wenjie Luo, Qun Song, Zhenyu Yan, Rui Tan, and Guosheng Lin. 2022. Indoor Smartphone SLAM with Learned Echoic Location Features. In SenSys.
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Qun Song, Chaojie Gu, and Rui Tan. 2018. Deep room recognition using inaudible echos. IMWUT 2, 3 (2018), 1–28.
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Statista. 2019. Value of the smartphone sensor market by type worldwide from 2010 to 2021 (in billion U.S. dollars). https://www.statista.com/statistics/934493/smartphone-sensor-market-by-type-worldwide/.
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Zhenyu Yan, Rui Tan, Qun Song, and Chris Xiaoxuan Lu. 2022. Telesonar: Robocall Alarm System by Detecting Echo Channel and Breath Timing. In SenSys.
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Published In
July 2023
173 pages
ISBN:9798400702334
DOI:10.1145/3603165
Copyright © 2023 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 25 September 2023
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- Refereed limited
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ACM TURC '23
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