| Title | Robot Hearing Through Optical Channel in a Cocktail Party Environment |
| Author | |
| Corresponding Author | Hong, Xiaoping |
| Publication Years | 2022-12-01
|
| DOI | |
| Source Title | |
| EISSN | 2640-4567
|
| Abstract | The cocktail party problem refers to a challenging process when the human sensory system tries to separate a specific voice from a loud mixture of background sound sources. The problem is much more demanding for machines and has become the holy grail in robotic hearing. Despite many advances in noise suppression, the intrinsic information from the contaminated acoustic channel remains difficult to recover. Herein, a simple-yet-powerful laser-assisted audio system termed robot ear accomplished by laser (REAL) is shown to probe the vibrations of sound-carrying surfaces (mask, throat, and other nearby surfaces) in optical channel, which is intrinsically immune to acoustic background noises. The results demonstrate that REAL can directly obtain the audio-frequency content from the laser without acoustic channel interference. The signals can be further transcribed into human-recognizable audios by exploiting the internal time and frequency correlations through memory-enabled neural networks. The REAL system would enable a new way in human-robot interaction. An interactive preprint version of the article can be found at: . |
| Keywords | |
| URL | [Source Record] |
| Indexed By | |
| Language | English
|
| SUSTech Authorship | First
; Corresponding
|
| Funding Project | SUSTech[Y01966105]
; DJI[K2096Z028]
|
| WOS Research Area | Automation & Control Systems
; Computer Science
; Robotics
|
| WOS Subject | Automation & Control Systems
; Computer Science, Artificial Intelligence
; Robotics
|
| WOS Accession No | WOS:000895333100001
|
| Publisher | |
| Data Source | Web of Science
|
| Citation statistics |
Cited Times [WOS]:0
|
| Document Type | Journal Article |
| Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/417087 |
| Department | School of System Design and Intelligent Manufacturing |
| Affiliation | Southern Univ Sci & Technol, Sch Syst Design & Intelligent Mfg, Shenzhen 518000, Peoples R China |
| First Author Affilication | School of System Design and Intelligent Manufacturing |
| Corresponding Author Affilication | School of System Design and Intelligent Manufacturing |
| First Author's First Affilication | School of System Design and Intelligent Manufacturing |
| Recommended Citation GB/T 7714 |
Guo, Xiao,Ding, Siyi,Peng, Ti,et al. Robot Hearing Through Optical Channel in a Cocktail Party Environment[J]. ADVANCED INTELLIGENT SYSTEMS,2022.
|
| APA |
Guo, Xiao,Ding, Siyi,Peng, Ti,Li, Kenan,&Hong, Xiaoping.(2022).Robot Hearing Through Optical Channel in a Cocktail Party Environment.ADVANCED INTELLIGENT SYSTEMS.
|
| MLA |
Guo, Xiao,et al."Robot Hearing Through Optical Channel in a Cocktail Party Environment".ADVANCED INTELLIGENT SYSTEMS (2022).
|
| Files in This Item: | There are no files associated with this item. | |||||
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