个性化头相关传输函数的近似获取——现状和问题

虚拟听觉重放采用头相关传输函数(HRTF)合成双耳声信号,并用耳机重放,以产生所需的空间听觉事件。理想的虚拟听觉重放需要个性化HRTF。个性化HRTF可通过实验测量或数值计算相对地准确获得。然而,测量每个潜在使用者的高空间分辨率HRTF是困难的,而数值计算HRTF的频段往往受限于计算机性能。近年发展了多种HRTF的近似获取方法,并成为热门研究课题,但效果有待验证和提高。本文评述了个性化HRTF近似的研究进展,指出了存在的问题和今后的方向。     

近场头相关传输函数的多声源快速测量系统设计与验证

近场头相关传输函数(HRTF)是双耳听觉科学研究和虚拟听觉重放应用的重要基础数据。近场HRTF测量系统要求具有高的测量效率、精度和重复性,以至于目前未见文献解决真人受试者的近场HRTF测量困难。本文研究并实现了一种计算机控制的近场HRTF的高效测量系统,并提出系统的快速校准方法,首先实现了真人受试者的近场HRTF测量。通过声学、机械与电子硬件和软件的综合设计,提高了测量效率。通过准确校准声源、受试者和双耳传声器的位置,提高了测量精确度和重复性。系统可用于1.0 m范围内不同声源距离的真人受试者以及人工头的近场HRTF测量,单个声源距离的全空间近场HRTF测量时间减少至20 min以内。测量结果表明,系统测量精度满足实际需求,可用于科学研究和个性化近场HRTF测量及数据库建立。      

重放自由场虚拟源距离信息的动态双耳Ambisonics方法

双耳重放的目标之一是在耳机重放中产生不同方向和距离的虚拟源感知。本文研究了动态双耳Ambisonics重放自由场虚拟源方向和距离信息的简化信号处理方法。该信号处理方法包括两步:第1步是基于目标声场的球谐函数分解,合成采用扬声器的近场Ambisonics重放中逐级重构目标声场的信号;第2步是采用虚拟扬声器重放的方法,用动态头相关函数滤波处理将Ambisonics的扬声器重放信号转换为双耳重放信号并用耳机重放。进一步研究了动态双耳Ambisonics的阶数对定位效果的影响,为简化信号处理提供依据。对重放产生的双耳声压分析表明,5阶动态双耳Ambisonics重放足以提供听觉方向定位和距离感知的重要信息。同时心理声学的实验结果表明,结合声源距离相关的响度因素,5阶动态双耳Ambisonics重放可产生不同方向和1.0 m以下不同近场距离的自由场虚拟源的听觉感知。本文的方法仅需要固定距离的48个均匀空间方向的远场非个性化HRTF处理,实现了信号处理的简化。      

头相关传递函数测试新方法

正头相关传递函数(Head-related transfer function,HRTF)描述了自由声场的声波从声源发出传播到双耳的过程中由于人体反射和散射引起的信号频谱改变。HRTF在双耳定位、虚拟声像合成以及串音消除的研究中发挥着重要的作用。在有关HRTF的研究工作中,HRTF数据库的获取是一个重要的问题。HRTF是高度个性化的。为了使得测试数据具有足够的空间分辨率,需要在一系列的仰角和方位角进     

头相关传输函数幅度谱的听觉空间分辨阈值的分析

提出一种分析头相关传输函数(head-related transfer function,HRTF)幅度谱的听觉空间分辨阈值模型。采用数值计算得到的高空间分辨率HRTF数据,计算了声源空间位置变化引起的HRTF幅度谱的变化,进一步利用Moore响度模型分析双耳响度级差、双耳响度级谱和总响度级等三个听觉感知量的变化。根据现有的3个听觉感知量最小可察觉差异,模型利用双耳响度级差和双耳响度级谱的变化得到的估计结果与心理声学实验一致,因此是一种有效预测听觉空间分辨阈值的方法,可用于为简化虚拟听觉信号处理和数据储存。      

头相关传输函数幅度谱的听觉空间分辨阈值的分析

提出一种分析头相关传输函数(head-related transfer function,HRTF)幅度谱的听觉空间分辨阈值模型。采用数值计算得到的高空间分辨率HRTF数据,计算了声源空间位置变化引起的HRTF幅度谱的变化,进一步利用Moore响度模型分析双耳响度级差、双耳响度级谱和总响度级等三个听觉感知量的变化。根据现有的3个听觉感知量最小可察觉差异,模型利用双耳响度级差和双耳响度级谱的变化得到的估计结果与心理声学实验一致,因此是一种有效预测听觉空间分辨阈值的方法,可用于为简化虚拟听觉信号处理和数据储存。     

5.1通路环绕声的耳机虚拟重放

提出了一种改进的5.1通路环绕声的耳机虚拟重放信号处理方法。在对现有的信号处理方法进行分析,指出它会产生不自然主观听觉效果后,通过理论和心理声学实验证明,采用HRTF信号处理、环绕声信号去相关等方法,在克服普通耳机声重放的“头中定位”的缺点、虚拟出多环绕扬声器效果的同时,并未带来新的不自然听觉效果。因此信号处理方法可增加听觉上的包围感,从而改善耳机重放的主观听觉效果。     

采用无耳壳头相关传输函数的虚拟声信号处理

本文提出采用无耳壳、封闭耳道的头相关传输函数（HRTF）进行虚拟声信号处理的方法。理论分析表明，在包含功率均衡的扬声器虚拟声信号处理中，采用无耳壳、封闭耳道的头相关传输函数可有效地减少信号处理函数的谷点，从而减少声重发的音色改变。心理声学的实验结果表明，新处理方法的声像定位与传统的带耳壳、耳道的HRTF处理无显著区别，但音色较后者有所改善。因而新的方法更适合实际的虚拟声信号处理应用。     

基于个体张量分解与模态的头相关传输函数重构

远场头相关传输函数(HRTF)随声源方向、频率以及个体变化。完整HRTF的数据量很大,且测量或计算每个人的高方向分辨率HRTF是很困难的。本文提出一种从少量方向的测量或计算重构高方向分辨率HRTF的方法。基于HRTF张量分解,远场HRTF可分解为方向模态、频率模态和少量个体模态的张量组合。通过对已有的基线HRTF数据库进行统计分析,可得到与个体无关的方向模态矩阵和频率模态矩阵。而对于任何新的个体,只要少量方向的测量或计算HRTF即可估计出个体模态的变化,并重构出高方向分辨率的HRTF数据。对两个HRTF数据库的计算表明,采用11个个体模态即可表示超过98%的个体相关的HRTF能量变化,并从大约30个方向的测量或计算HRTF重构出高方向分辨率的HRTF幅度。心理声学实验验证了提出的方法。该方法可用于简化个性化HRTF的测量或计算。     

扬声器的特性不匹配对虚拟声像的影响

本文从理论和实验上探讨了扬声器的特性不匹配对重放虚拟声像的影响。结果表明,用两扬声器进行虚拟听觉重放时,在某些频率段和虚拟声像角度,两扬声器间很小的幅频特性差异或相频特性差异都足以对虚拟声像方向产生明显的影响。扬声器特性的差异对前方范围的声像影响较小,但对侧向范围的声像影响较大,因而两扬声器的特性不匹配也是导致虚拟听觉重放时侧向声像位置畸变的重要原因之一。而在实际应用中要特别注意两扬声器的特性匹配,或者要用信号处理的方法对两扬声器的特性进行校正。     

Influence of measurement methodology of head-related transfer functions on auditory perception

Head-related transfer functions(HRTFs) are the core of virtual auditory display and relevant applications. However,a standard method for HRTF measurements has not been established. This work examines the influence of different HRTF measurement methodologies on auditory perception. First, the diffusion-field equalization was proposed and applied to HRTFs of a single dummy head(KEMAR) from five different datasets. Then,the spectral deviations among the HRTFs were calculated and analyzed. Finally, a series of subjective listening experiments(including localization and discrimination experiments) were conducted. Results indicate the diffusion-field equalization is an effective pre-processing method which reduces the difference in HRTF magnitude spectra caused by different measurement methodologies. Moreover,the HRTFs from different measurement methodologies have similar localization performance below 12 kHz, whereas the inter-dataset differences in timbre are distinct leading to audible discrimination.     

HRTF personalization based on artificial neural network in individual virtual auditory space

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.     

A hybrid algorithm for selecting head-related transfer function based on similarity of anthropometric structures

As the basic data for virtual auditory technology, head-related transfer function (HRTF) has many applications in the areas of room acoustic modeling, spatial hearing and multimedia. How to individualize HRTF fast and effectively has become an opening problem at present. Based on the similarity and relativity of anthropometric structures, a hybrid HRTF customization algorithm, which has combined the method of principal component analysis (PCA), multiple linear regression (MLR) and database matching (DM), has been presented in this paper. The HRTFs selected by both the best match and the worst match have been applied into obtaining binaurally auralized sounds, which are then used for subjective listening experiments and the results are compared. For the area in the horizontal plane, the localization results have shown that the selection of HRTFs can enhance the localization accuracy and can also abate the problem of front-back confusion.     

Fast head-related transfer function measurement via reciprocity

An efficient method for head-related transfer function (HRTF) measurement is presented. By applying the acoustical principle of reciprocity, one can swap the speaker and the microphone positions in the traditional (direct) HRTF measurement setup, that is, insert a microspeaker into the subject's ear and position several microphones around the subject, enabling simultaneous HRTF acquisition at all microphone positions. The setup used for reciprocal HRTF measurement is described, and the obtained HRTFs are compared with the analytical solution for a sound-hard sphere and with KEMAR manikin HRTF obtained by the direct method. The reciprocally measured sphere HRTF agrees well with the analytical solution. The reciprocally measured and the directly measured KEMAR HRTFs are not exactly identical but agree well in spectrum shape and feature positions. To evaluate if the observed differences are significant, an auditory localization model based on work by J. C. Middlebrooks [J. Acoust. Soc. Am. 92, 2607-2624 (1992)] was used to predict where a virtual sound source synthesized with the reciprocally measured HRTF would be localized if the directly measured HRTF were used for the localization. It was found that the predicted localization direction generally lies close to the measurement direction, indicating that the HRTFs obtained via the two methods are in good agreement.     

Sensitivity of human subjects to head-related transfer-function phase spectra.

Head-related transfer functions (HRTFs) for human subjects in anechoic space were modeled with modified phase spectra, including minimum-phase-plus-delay, linear-phase, and reversed-phase-plus-delay functions. The overall (wide-band) interaural time delay (ITD) for the modeled HRTFs was made consistent with that of the empirical HRTFs by setting the position-dependent, frequency-independent delay in the HRTF for the lagging ear. Signal analysis of the minimum-phase-plus-delay reconstructions indicated that model HRTFs deviate from empirical HRTF measurements maximally for contralateral azimuths and low elevations. Subjects assessed the perceptual validity of the model HRTFs in a four-interval, two-alternative, forced-choice discrimination paradigm. Results indicate that monaural discrimination performance of subjects was at chance for all three types of HRTF models. Binaural discrimination performance was at chance for the linear-phase HRTFs, was above chance for some locations for the minimum-phase-plus-delay HRTFs, and was above chance for all tested locations for the reversed-phase-plus-delay HRTFs. An analysis of low-frequency timing information showed that all of these results are consistent with efficient use of interaural time differences in the low-frequency components of the stimulus waveforms. It is concluded that listeners are insensitive to HRTF phase spectra as long as the overall ITD of the low-frequency components does not provide a reliable cue. In particular, the minimum-phase-plus-delay approximation to the HRTF phase spectrum is an adequate approximation as long as the low-frequency ITD is appropriate. These results and conclusions are all limited to the anechoic case when the HRTFs correspond to brief impulse responses limited to a few milliseconds.     

Recovery of individual head-related transfer functions from a small set of measurements

Head-related transfer functions (HRTFs) vary with individuals, and in practice, measuring HRTFs with high directional resolution for each individual is tiresome. Based on a basis functions representation of HRTFs, the present work proposes a method for recovering individual HRTFs from a small set of measurements. The HRTFs are represented by a combination of a small set of spatial basis functions (SBFs) with frequency- and individual-dependent weights. The SBFs are derived by applying spatial principal component analysis to a baseline HRTF dataset with high directional resolution. The individual weights for any subject outside the dataset are estimated from measurements at a few source directions, and then the HRTFs with high directional resolution are recovered by combining the SBFs and the individual weights. In an illustrative case, the SBFs derived from a baseline dataset that includes 20 subjects are used to recover the HRTF magnitudes for six subjects outside the baseline dataset. Results show that individual HRTF magnitudes can be recovered from measurements at 73 directions with a mean signal-to-distortion ratio of 19 dB. The proposed method is also applicable to recovering head-related impulse responses. The results of psychoacoustic experiments indicate that in most cases the recovered and measured HRTFs are indistinguishable.     

A model of head-related transfer functions based on principal components analysis and minimum-phase reconstruction.

Free-field to eardrum transfer functions (HRTFs) were measured from both ears of 10 subjects with sound sources at 265 different positions. A principal components analysis of the resulting 5300 HRTF magnitude functions revealed that the HRTFs can be modeled as a linear combination of five basic spectral shapes (basis functions), and that this representation accounts for approximately 90% of the variance in the original HRTF magnitude functions. HRTF phase was modeled by assuming that HRTFs are minimum-phase functions and that interaural phase differences can be approximated by a simple time delay. Subjects' judgments of the apparent directions of headphone-presented sounds that had been synthesized from the modeled HRTFs were nearly identical to their judgments of sounds synthesized from measured HRTFs. With fewer than five basis functions used in the model, a less faithful reconstruction of the HRTF was produced, and the frequency of large localization errors increased dramatically.     

Median plane localization using a parametric model of the head-related transfer function based on spectral cues

To examine a simulation method for vertical sound localization, and to clarify which peaks and notches in head-related transfer functions (HRTFs) play a role as spectral cues, localization tests in the median plane were carried out using a parametric HRTF model, which is recomposed only of extracted spectral peaks and notches. The results show that the parametric HRTF recomposed using the first and second notches (N1 and N2) and the first peak (P1) provides almost the same localization accuracy as the measured HRTFs. Observations of the spectral peaks and notches indicate that N1 and N2 change remarkably as the source elevation changes, whereas P1 does not depend on the source elevation. In conclusion, N1 and N2 can be regarded as spectral cues, and the hearing system could utilize P1 as the reference information to analyze N1 and N2.     

Design and validation on a multiple sound source fast-measurement system of near-field head-related transfer functions

Near-field head-related transfer functions(HRTFs) are essential to scientific researches of binaural hearing and practical applications of virtual auditory display. High efficiency, accuracy and repeatability are required in a near-field HRTF measurement. Hence,there is no reference which intents on solving the measuring difficulties of near-field HRTF for human subjects. In present work, an efficient near-field HRTF measurement system based on computer control is designed and implemented, and a fast calibration method for the system is proposed to first solve the measurement of near-field HRTF for human subjects. The efficiency of measurement is enhanced by a comprehensive design on the acoustic, electronic and mechanical parts of the system. And the accuracy and repeatability of the measurement are greatly improved by carefully calibrating the positions of sound source, subject and binaural microphones.This system is suitable for near-field HRTF measurement at various source distances within 1.0 m, for both human subject and artificial head. The time costs of HRTF measurement at a single sound source distance and full directions has been reduced to less than 20 minutes. The measurement results indicate that the accuracy of the system satisfies the actual requirements.The system is applicable to scientific research and can be used to establish an individualized near-field HRTF database for human subjects.     

Estimation of interaural level difference based on anthropometry and its effect on sound localization

Individualization of head-related transfer functions (HRTFs) is important for highly accurate sound localization systems such as virtual auditory displays. A method to estimate interaural level differences (ILDs) from a listener's anthropometry is presented in this paper to avoid the burden of direct measurement of HRTFs. The main result presented in this paper is that localization is improved with nonindividualized HRTF if ILD is fitted to the listener. First, the relationship between ILDs and the anthropometric parameters was analyzed using multiple regression analysis. The azimuthal variation of the ILDs in each 1/3-octave band was then estimated from the listener's anthropometric parameters. A psychoacoustical experiment was carried out to evaluate its effectiveness. The experimental results show that the adjustment of the frequency characteristics of ILDs for a listener with the proposed method is effective for localization accuracy.