首页 | 本学科首页   官方微博 | 高级检索  
     检索      


HRTF personalization based on artificial neural network in individual virtual auditory space
Authors:Hongmei Hu  Lin Zhou
Institution:a School of Information Science and Engineering, Southeast University, 210096 Nanjing, China
b School of Mechanical Engineering, Jiangsu University, 210013 Zhenjiang, China
Abstract:The synthesis of individual virtual auditory space (VAS) is an important and challenging task in virtual reality. One of the key factors for individual VAS is to obtain a set of individual head related transfer functions (HRTFs). A customization method based on back-propagation (BP) artificial neural network (ANN) is proposed to obtain an individual HRTF without complex measurement. The inputs of the neural network are the anthropometric parameters chosen by correlation analysis and the outputs are the characteristic parameters of HRTFs together with the interaural time difference (ITD). Objective simulation experiments and subjective sound localization experiments are implemented to evaluate the performance of the proposed method. Experiments show that the estimated non-individual HRTF has small mean square error, and has similar perception effect to the corresponding one obtained from the database. Furthermore, the localization accuracy of personalized HRTF is increased compared to the non-individual HRTF.
Keywords:Virtual auditory space  Artificial neural network  Head related transfer function  Head related impulse response  Interaural time difference  Sound localization
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号