Title
Improving the Localization Accuracy of Virtual Sound Source through Reinforcement Learning
Abstract
Localization of virtual sound source is a technology that allows the reproducing of three-dimensional sounds using stereo earphones, and applications of this technology in Brain-machine interface that use auditory stimuli are being investigated. In order to achieve virtual sounds using this technology, the Head-related Transfer Function (HRTF) of the user must be measured accurately. The HRTF can be measured accurately with the appropriate placement of the microphones and measurement environment, but procuring an ideal setup is usually difficult. To overcome this, we instead attempt to obtain an accurate HRTF using reinforcement learning. We performed simulations and verified that with the proposed method the HRTF accuracy improved on 24 horizontal directions. Also, in online learning experiments, the localization accuracy was improved for 3 subjects, suggesting the validity of our method.
Year
DOI
Venue
2013
10.1109/SMC.2013.747
Systems, Man, and Cybernetics
Keywords
Field
DocType
virtual sound source,appropriate placement,accurate hrtf,localization accuracy,hrtf accuracy,head-related transfer function,reinforcement learning,virtual sound,brain-machine interface,learning artificial intelligence,audio signal processing,brain computer interfaces
Online learning,Auditory stimuli,Computer science,Brain–computer interface,Speech recognition,Transfer function,Audio signal processing,Reinforcement learning
Conference
ISSN
Citations 
PageRank 
1062-922X
0
0.34
References 
Authors
2
6
Name
Order
Citations
PageRank
Manabu Washizu100.34
Shuhei Morioka200.68
Isao Nambu3147.58
Shohei Yano441.29
Haruhide Hokari552.03
Yasuhiro Wada622562.58