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中文核心期刊

一种快速合成多虚拟声源的头相关传输函数模型

A head-related transfer function model for fast synthesizing multiple virtual sound sources

  • 摘要: 提出了一种用于实时快速合成多个虚拟声源的头相关传输函数(HRTF)模型。首先对水平面的头相关脉冲响应(HRIR,头相关传输函数的时域形式)数据进行两层小波包分解,然后用一组子带滤波器和综合滤波器建立模型。子带滤波器的系数由HRIR小波系数的零插值得到,综合滤波器的系数由小波函数计算得到。通过使用阈值法对小波系数进行压缩,即可达到简化模型、减小运算量的目的。计算表明,只需要使用30点的小波系数建模,可使模型的重构误差控制在1%的量级。而心理声学实验表明,使用35点的小波系数,模型可得到和原始的HRTF滤波器相当的听觉效果。在同时合成多个虚拟声源的实时计算中,模型的运算量明显小于普通的HRTF滤波器。

     

    Abstract: A head-related transfer function(HRTF) model for fast and real-time synthesizing multiple virtual sound sources is proposed.Firstly,a HRIR(head-related impulse response,the time domain version of the HRTF) is decomposed by using a 2-level wavelet packet and then represented by a model composed of subband filters and reconstruction filters. The coefficients of the subband filters are the zero interpolation of the wavelet coefficients of the HRIR.The coefficients of the reconstruction filters can be calculated from the wavelet function.The model is simplified by applying a threshholding method to reduce the wavelet coefficients.The calculated results indicate that for a model with 30 wavelet coefficients, the error in reconstructed HRIR is about 1%.And the result of a psychoacoustic test shows that a model with 35 wavelet coefficients is indistinguishable from the original HRIR in hearing.When multiple virtual sound images are synthesized at the same time,the computational load of the proposed model is much less than the traditional HRTF filter.

     

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