中垂面谱特征的提取和建模
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摘要
头相关传输函数表征了声源到耳的传输特性,在虚拟声重放及其相关领域具有广泛的应用.针对头相关传输函数的多维特征,提出了基于独立成分分析的中垂面谱特征的提取和建模方法,并采用主观辨别实验验证了模型的听觉有效性.计算结果表明,中垂面的平均谱失真随着展开阶数的增加呈逐渐下降的趋势,前6阶独立成分的计权组合可有效表征中垂面谱的主要特征.实验结果表明,在±45°的仰角范围内,文中提出的中垂面谱模型不会引起听觉感知的畸变.
Head-related transfer functions(HRTFs),which represent the sound transmission process from sound sources to human ears,are widely used in virtual sound reproduction and relevant fields. In order to utilize the multiple dimensionalities of HRTFs,an extraction and modeling method of median-plane spectral characteristics is proposed on the basis of independent component analysis( ICA). Moreover,a subjective discrimination experiment is carried out to validate the applicability of the proposed model. Calculation results show that the mean value of median-plane spectral distortion decreases gradually with the rise of expansion order,and a weighted combination of the preceding six-expansion components represents the main part of median-plane spectral characteristics.Furthermore,experimental results show that no auditory degradation is perceived when the proposed ICA-based median-plane spectral model is employed at the elevations from 45° to-45°.
Head-related transfer functions(HRTFs),which represent the sound transmission process from sound sources to human ears,are widely used in virtual sound reproduction and relevant fields. In order to utilize the multiple dimensionalities of HRTFs,an extraction and modeling method of median-plane spectral characteristics is proposed on the basis of independent component analysis( ICA). Moreover,a subjective discrimination experiment is carried out to validate the applicability of the proposed model. Calculation results show that the mean value of median-plane spectral distortion decreases gradually with the rise of expansion order,and a weighted combination of the preceding six-expansion components represents the main part of median-plane spectral characteristics.Furthermore,experimental results show that no auditory degradation is perceived when the proposed ICA-based median-plane spectral model is employed at the elevations from 45° to-45°.
引文
[1] BLAUERT J. Spatial hearing(revised edition)[M]. Cambridge:MIT Press,1997.
[2] XIE B S. Head-related transfer function and virtual auditory display[M]. New York:J Ross Publishing,2013.
[3]钟小丽,谢菠荪.头相关传输函数的研究进展(一)[J].电声技术,2004(12):44-46.ZHONG Xiao-li,XIE Bo-sun. Advances in head-related transfer function:I[J]. Audio Engineering,2004(12):44-46.
[4]余光正,何颖洋,李哲林.个性化耳廓旋转角测量与头相关传输函数定制[J].华南理工大学学报(自然科学版),2016,44(7):135-141.YU Guang-zheng,HE Ying-yang,LI Zhe-lin. Measurement of individual pinna rotation angle and customization of head-related transfer functions[J]. Journal of South China University of Technology(Natural Science Edition),2016,44(7):135-141.
[5] KISTLER D J,WIGHTMAN F L. A model of head-related transfer functions based on principal components analysis and minimum-phase reconstruction[J]. The Journal of the Acoustical Society of America,1992,91(3):1637-1647.
[6] KIMBERLY J F,LAURA R. Individualization of head related transfer functions using principal component analysis[J]. Applied Acoustics,2015,87:162-173.
[7] HWANG S,PARK Y. Interpretations on principal components analysis of head related impulse responses in the median plane[J]. The Journal of the Acoustical Society of America,2008,123(4):EL65-EL71.
[8] HWANG S,PARK Y. HRIR customization in the median plane via principal components analysis[C]∥Proceedings of AES the 31st International Conference. London:Audio Engineering Society,2007:No. 9/1-7.
[9] ZHONG X L,PENG C C. Individualization of head-related transfer function based on multiple databases[C]∥Proceedings of Inter-noise and Noise-con Congress and Conference. Hong Kong:Institude of Noise Control Engineering,2017:5571-5577.
[10] BARTLETT M S,MOVELLAN J R,SEJNOWSKI T J.Face recognition by independent component analysis[J]. IEEE Transactions on Neural Networks,2002,13(6):1450-1464.
[11] HYVRINEN A,KARHUNEN J,OJA E.独立成分分析[M].周宗潭,董国华,徐昕,等译.北京:电子工业出版社,2007.
[12] HYVRINEN A,OJA E. Independent component analysis:algorithms and applications[J]. Neural Networks,2000,13(4/5):411-430.
[13] LARCHER V,JOT J M,GUYARD J,et al. Study and comparison of efficient methods for 3-D audio spatialization based on linear decomposition of HRTF data[C]∥Proceedings of the 108th Audio Engineering Society Convention. Paris:Audio Engineering Society,2000:5097/1-30.
[14] HYVRINEN A. Fast and robust fixed point for independent component analysis[J]. IEEE Transactions on Neural Networks,1999,10(3):626-634.
[15]刘雪洁.基于生理参数的头相关传输函数的定制[D].广州:华南理工大学,2014.
[16] ALGAZI V R,DUDA R O,THOMPSON D M,et al. The CIPIC HRTF database[C]∥Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. New Paltz:IEEE,2001:99-102.
[2] XIE B S. Head-related transfer function and virtual auditory display[M]. New York:J Ross Publishing,2013.
[3]钟小丽,谢菠荪.头相关传输函数的研究进展(一)[J].电声技术,2004(12):44-46.ZHONG Xiao-li,XIE Bo-sun. Advances in head-related transfer function:I[J]. Audio Engineering,2004(12):44-46.
[4]余光正,何颖洋,李哲林.个性化耳廓旋转角测量与头相关传输函数定制[J].华南理工大学学报(自然科学版),2016,44(7):135-141.YU Guang-zheng,HE Ying-yang,LI Zhe-lin. Measurement of individual pinna rotation angle and customization of head-related transfer functions[J]. Journal of South China University of Technology(Natural Science Edition),2016,44(7):135-141.
[5] KISTLER D J,WIGHTMAN F L. A model of head-related transfer functions based on principal components analysis and minimum-phase reconstruction[J]. The Journal of the Acoustical Society of America,1992,91(3):1637-1647.
[6] KIMBERLY J F,LAURA R. Individualization of head related transfer functions using principal component analysis[J]. Applied Acoustics,2015,87:162-173.
[7] HWANG S,PARK Y. Interpretations on principal components analysis of head related impulse responses in the median plane[J]. The Journal of the Acoustical Society of America,2008,123(4):EL65-EL71.
[8] HWANG S,PARK Y. HRIR customization in the median plane via principal components analysis[C]∥Proceedings of AES the 31st International Conference. London:Audio Engineering Society,2007:No. 9/1-7.
[9] ZHONG X L,PENG C C. Individualization of head-related transfer function based on multiple databases[C]∥Proceedings of Inter-noise and Noise-con Congress and Conference. Hong Kong:Institude of Noise Control Engineering,2017:5571-5577.
[10] BARTLETT M S,MOVELLAN J R,SEJNOWSKI T J.Face recognition by independent component analysis[J]. IEEE Transactions on Neural Networks,2002,13(6):1450-1464.
[11] HYVRINEN A,KARHUNEN J,OJA E.独立成分分析[M].周宗潭,董国华,徐昕,等译.北京:电子工业出版社,2007.
[12] HYVRINEN A,OJA E. Independent component analysis:algorithms and applications[J]. Neural Networks,2000,13(4/5):411-430.
[13] LARCHER V,JOT J M,GUYARD J,et al. Study and comparison of efficient methods for 3-D audio spatialization based on linear decomposition of HRTF data[C]∥Proceedings of the 108th Audio Engineering Society Convention. Paris:Audio Engineering Society,2000:5097/1-30.
[14] HYVRINEN A. Fast and robust fixed point for independent component analysis[J]. IEEE Transactions on Neural Networks,1999,10(3):626-634.
[15]刘雪洁.基于生理参数的头相关传输函数的定制[D].广州:华南理工大学,2014.
[16] ALGAZI V R,DUDA R O,THOMPSON D M,et al. The CIPIC HRTF database[C]∥Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. New Paltz:IEEE,2001:99-102.