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【学术讲座预告】——WaveEar: Exploring a mmWave-based Noise-resistant Speech Sensing for Voice-User Interface
发布时间:2018-10-14

讲者简介

王堃,UCLA高级研究教授。于20097月和20182月分别在南京邮电大学信息安全专业和日本会津大学计算机科学与工程专业获得双博士学位,2010年获江苏省百篇优秀博士学位论文奖。2009年在南京邮电大学物联网学院任教,破格晋升副教授,2017年晋升教授。2013年至2015年在美国加州大学洛杉矶分校(UCLA)从事博士后研究,2017年至2018年在香港理工大学计算学系担任助理研究员。主持国家自然科学基金3项,主要研究领域为物联网、数据中心、区块链和分布式系统等,在主要会议和期刊上发表论文150余篇,包括ieee-tiptctpdstontmcacm-ubicompacm-mobisysacm-sensysieee-icdcsieee-ipdps以及12esi高引用论文。获得IEEEGlobecom 2016IEEETCGCC 2018IEEETCBD 2019IEEEISJIEEESystems Journal2019CBD1994项最佳论文奖。同时担任IEEE Access副主编,《网络与计算机应用杂志》主编,IEEE NetworkIEEE Access、下一代计算机系统、p2p网络与应用等客座编辑。

 

摘要 

DVoice-user interface (VUI) has become an integral component in modern personal devices (e.g., smartphones, voice assistant) by fundamentally evolving the information sharing between the user and device. Acoustic sensing for VUI is designed to sense all acoustic objects; however, the existing VUI mechanism can only offer low quality speech sensing. This is due to the audible and inaudible interference from complex ambient noise that limits the performance of VUI by causing denial-of-service (DoS) of user requests. Therefore, it is of paramount importance to enable noise-resistant speech sensing in VUI for executing critical tasks with superior efficiency and precision in robust environments. To this end, we investigate the feasibility of employing radio-frequency signals, such as millimeter wave (mmWave) for sensing the noise-resistant voice of an individual. We first perform an in-depth study behind the rationale of voice generation and resulting vocal vibrations. From the obtained insights, we present WaveEar, an end-to-end noise-resistant speech sensing system. WaveEar comprises a lowcost mmWave probe to localize the position of the speaker among multiple people and direct the mmWave signals towards the nearthroat region of the speaker for sensing his/her vocal vibrations. The received signal, containing the speech information, is fed to our novel deep neural network for recovering the voice through exhaustive extraction. Our experimental evaluation under real-world scenarios with 21 participants shows the effectiveness of WaveEar to precisely infer the noise-resistant voice and enable a pervasive VUI in modern electronic devices.

 

讲座时间

20191017日(星期)上午1030

讲座地点

闽江学院工科大楼A5楼重点实验室会议室

主办单位:泛亚电竞官网  

计算机与控制工程学院

承办单位 

福建省信息处理与智能控制重点实验室 

协办单位

数字福建智能化生产物联网实验室

电子信息与控制工程研究中心

工业机器人应用福建省高校工程研究中心

福州市机器人技术应用联合实验室

闽江学院互联网创新研究中心

闽江学院汇川科技物联网联合研究院

闽江学院计算机与控制技术研究所

闽江学院2011协同创新培育点物联网技术与智能系统

 

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