Method to Extrapolate HRTF at Low Elevation of Median Plane by Means of Neural Network

Journal of South China University of Technology (Natural Science Edition) ›› 2007, Vol. 35 ›› Issue (9): 20-25.

• Electronics, Communication & Automation Technology • Previous Articles Next Articles

Method to Extrapolate HRTF at Low Elevation of Median Plane by Means of Neural Network

Zhong Xiao-li

School of Physical Science and Technology , South China Univ. of Techn. , Guangzhou 510640 , Guangdong , China

Received:2006-10-12 Online:2007-09-25 Published:2007-09-25
Contact: 钟小丽(1975-) ，女，博士，讲师，主要从事音频信号处理和电声技术方面的研究. E-mail:xlzhong@ scut.edu. cn
About author:钟小丽(1975-) ，女，博士，讲师，主要从事音频信号处理和电声技术方面的研究.
Supported by:
国家自然科学基金资助项目(1 0374031 )

Abstract

Abstract:

In order to construct a continuous head-related transfer function (HRTF) along elevation , a method to extrapolate the HRTF at low elevation of the median plane is proposed based on the radial basis function (RBF) neural network. Then , according to the data of KEMAR mannequin and a human being , the performances of the proposed method in three network input methods are analyzed. The results show that the correlative coefficient between he extrapolated and the measured HRTFs is as high as O. 93 , that the extrapolation accuracy can be improved by increasing the data of network input and by reducing the spatial distance between the extrapolated and the known directions , and that the extrapolation error increases with frequency.

Key words: head-related transfer function, extrapolation, neural network, virtual reality

Zhong Xiao-li. Method to Extrapolate HRTF at Low Elevation of Median Plane by Means of Neural Network[J]. Journal of South China University of Technology (Natural Science Edition), 2007, 35(9): 20-25.

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Method to Extrapolate HRTF at Low Elevation of Median Plane by Means of Neural Network

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