Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/630805
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dc.contributor.authorGuanhua Wangen_US
dc.contributor.authorYongpan Zouen_US
dc.contributor.authorZimu Zhouen_US
dc.contributor.authorKaishun Wuen_US
dc.contributor.authorLionel M. Nien_US
dc.date.accessioned2020-05-20T09:47:42Z-
dc.date.available2020-05-20T09:47:42Z-
dc.date.issued2016en_US
dc.identifier.issn1536-1233en_US
dc.identifier.other10.1109/TMC.2016.2517630en_US
dc.identifier.urihttp://localhost/handle/Hannan/182490en_US
dc.identifier.urihttp://localhost/handle/Hannan/630805-
dc.descriptionen_US
dc.description.abstractRecent literature advances Wi-Fi signals to “see” people's motions and locations. This paper asks the following question: Can Wi-Fi “hear” our talks? We present WiHear, which enables Wi-Fi signals to “hear” our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micro-movement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can “hear” people talks within the radio range. Further, WiHear can simultaneously “hear” multiple people's talks leveraging MIMO technology. We implement WiHear on both USRP N210 platform and commercial Wi-Fi infrastructure. Results show that within our pre-defined vocabulary, WiHear can achieve detection accuracy of 91 percent on average for single individual speaking no more than six words and up to 74 percent for no more than three people talking simultaneously. Moreover, the detection accuracy can be further improved by deploying multiple receivers from different angles.en_US
dc.publisherIEEEen_US
dc.relation.haspart7384744.pdfen_US
dc.subjectmoving pattern recognition|Wi-Fi radar|interference cancelation|micro-motion detectionen_US
dc.titleWe Can Hear You with Wi-Fi!en_US
dc.typeArticleen_US
dc.journal.volume15en_US
dc.journal.issue11en_US
dc.journal.titleIEEE Transactions on Mobile Computingen_US
Appears in Collections:2016

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Full metadata record
DC FieldValueLanguage
dc.contributor.authorGuanhua Wangen_US
dc.contributor.authorYongpan Zouen_US
dc.contributor.authorZimu Zhouen_US
dc.contributor.authorKaishun Wuen_US
dc.contributor.authorLionel M. Nien_US
dc.date.accessioned2020-05-20T09:47:42Z-
dc.date.available2020-05-20T09:47:42Z-
dc.date.issued2016en_US
dc.identifier.issn1536-1233en_US
dc.identifier.other10.1109/TMC.2016.2517630en_US
dc.identifier.urihttp://localhost/handle/Hannan/182490en_US
dc.identifier.urihttp://localhost/handle/Hannan/630805-
dc.descriptionen_US
dc.description.abstractRecent literature advances Wi-Fi signals to “see” people's motions and locations. This paper asks the following question: Can Wi-Fi “hear” our talks? We present WiHear, which enables Wi-Fi signals to “hear” our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micro-movement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can “hear” people talks within the radio range. Further, WiHear can simultaneously “hear” multiple people's talks leveraging MIMO technology. We implement WiHear on both USRP N210 platform and commercial Wi-Fi infrastructure. Results show that within our pre-defined vocabulary, WiHear can achieve detection accuracy of 91 percent on average for single individual speaking no more than six words and up to 74 percent for no more than three people talking simultaneously. Moreover, the detection accuracy can be further improved by deploying multiple receivers from different angles.en_US
dc.publisherIEEEen_US
dc.relation.haspart7384744.pdfen_US
dc.subjectmoving pattern recognition|Wi-Fi radar|interference cancelation|micro-motion detectionen_US
dc.titleWe Can Hear You with Wi-Fi!en_US
dc.typeArticleen_US
dc.journal.volume15en_US
dc.journal.issue11en_US
dc.journal.titleIEEE Transactions on Mobile Computingen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7384744.pdf2.06 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGuanhua Wangen_US
dc.contributor.authorYongpan Zouen_US
dc.contributor.authorZimu Zhouen_US
dc.contributor.authorKaishun Wuen_US
dc.contributor.authorLionel M. Nien_US
dc.date.accessioned2020-05-20T09:47:42Z-
dc.date.available2020-05-20T09:47:42Z-
dc.date.issued2016en_US
dc.identifier.issn1536-1233en_US
dc.identifier.other10.1109/TMC.2016.2517630en_US
dc.identifier.urihttp://localhost/handle/Hannan/182490en_US
dc.identifier.urihttp://localhost/handle/Hannan/630805-
dc.descriptionen_US
dc.description.abstractRecent literature advances Wi-Fi signals to “see” people's motions and locations. This paper asks the following question: Can Wi-Fi “hear” our talks? We present WiHear, which enables Wi-Fi signals to “hear” our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micro-movement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can “hear” people talks within the radio range. Further, WiHear can simultaneously “hear” multiple people's talks leveraging MIMO technology. We implement WiHear on both USRP N210 platform and commercial Wi-Fi infrastructure. Results show that within our pre-defined vocabulary, WiHear can achieve detection accuracy of 91 percent on average for single individual speaking no more than six words and up to 74 percent for no more than three people talking simultaneously. Moreover, the detection accuracy can be further improved by deploying multiple receivers from different angles.en_US
dc.publisherIEEEen_US
dc.relation.haspart7384744.pdfen_US
dc.subjectmoving pattern recognition|Wi-Fi radar|interference cancelation|micro-motion detectionen_US
dc.titleWe Can Hear You with Wi-Fi!en_US
dc.typeArticleen_US
dc.journal.volume15en_US
dc.journal.issue11en_US
dc.journal.titleIEEE Transactions on Mobile Computingen_US
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7384744.pdf2.06 MBAdobe PDFThumbnail
Preview File