Issue |
JNWPU
Volume 36, Number 2, April 2018
|
|
---|---|---|
Page(s) | 281 - 286 | |
DOI | https://doi.org/10.1051/jnwpu/20183620281 | |
Published online | 03 July 2018 |
Personalization Method for HRTF Based on Multi-Dimensional Physiological Parameters
基于多维生理参数的头相关传递函数个人化方法
School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China
Received:
1
April
2017
Head-Related Transfer Function (HRTF) is the most important factor to achieve Auditory Space Modeling(ASM). HRTF has many applications in the areas of room acoustic modeling, spatial hearing and multimedia. For the reason that HRTF is related to the location and frequency of sound source and the physiological structures of the listener, customization of HRTF becomes the bottle-neck problem of the research and application of ASM. This paper, based on the measured data offers the personalization method of the HRTF based on the multi-dimensional physiological parameters, and the method is verified through the spectral distortion and the subjective auditory localization experiments. The results show that database matching can obtain the personalized HRTF efficiently and in the spatial hearing experiment the personalized HRTF can reduce the front-back confusion of auditory localization and improve the accuracy.
摘要
头相关传递函数(HRTF)是实现听觉空间虚拟的关键函数,不仅与声源的相对方位、频率有关,还与听者的生理结构有密切的关系,这使得其个人化(personalization)成为相关应用中的瓶颈问题。为此,以实测HRTF和多维生理参数数据为基础,结合相关分析、主成分分析和数据库匹配算法,给出了一种个人化方法,并通过谱失真(SD)以及主观听觉实验对算法的有效性进行评价和验证。结果表明,基于最小距离准则的数据库匹配方法是实现HRTF个人化预测的一种有效方法;基于多维实测生理参数获得的个人化HRTF数据相比于基于人工头的HRTF数据,能提高定位准确率4.6%,降低前后混淆率2.2%。
Key words: HRTF / personalization / anthropometrics / correlation analysis / principal component analysis / database matching / auditory location
关键字 : HRTF / 个人化 / 生理参数 / 相关性分析 / 主成分分析 / 数据库匹配 / 听觉定位
© 2018 Journal of Northwestern Polytechnical University. All rights reserved.
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