Head-related Transfer Function Measurement Research Articles

Comparative Analysis of HRTFs Measurement Using In-Ear Microphones.

The head-related transfer functions (HRTFs) describe the acoustic path transfer functions between sound sources in the free-field and the listener's ear canal. They enable the evaluation of the sound perception of a human being and the creation of immersive virtual acoustic environments that can be reproduced over headphones or loudspeakers. HRTFs are strongly individual and they can be measured by in-ear microphones worn by real subjects. However, standardized HRTFs can also be measured using artificial head simulators which standardize the body dimensions. In this paper, a comparative analysis of HRTF measurement using in-ear microphones is presented. The results obtained with in-ear microphones are compared with the HRTFs measured with a standard head and torso simulator, investigating different positions of the microphones and of the sound source and employing two different types of microphones. Finally, the HRTFs of five real subjects are measured and compared with the ones measured by the microphones in the ear of a standard mannequin.

Universal global compact representation of head-related transfer functions with hemi-spherical harmonics and conformal mapping

The head-related transfer function(HRTF) is an essential part of spatial auditory display systems. In recent years, numerous HRTF databases are established to include human subjects' measurements, which enabled data-driven research projects such as HRTF prediction and personalization. However, in most cases, each HRTF database has its own unique measuring standard and source direction grid set. It's difficult to merge and efficiently represent the global HRTF information across multiple HRTF databases. Current presentation methods, such as principle component analysis (PCA) and spherical harmonics transform (SHT), are constrained by the source grid layout and regularization errors, which lays burdens for common feature extraction from different sets of HRTF measurements. In this work, we propose a novel approach for the global compact representation of HRTFs across different measuring standards, using hemispherical harmonics (HSH) and conformal mapping. The method takes into account the spatial domain covered by the typical HRTF measurements and proves to be less contained by the source direction grids. Both numerical and auditory model experiments are performed, to examine the representation error and consistency when including multiple HRTF databases with different measuring standards and grid layouts. In continuing work, we are using this method as a pre-processing approach for HRTF personalization utilizing multiple HRTF databases.

Quantifying the impact of hearing-aid microphone placement and head-mounted devices on binaural cues from head-related transfer functions

Emerging techniques for assessment and training of spatial hearing use virtual reality (VR) devices to present auditory-visual cues. Sounds may be processed using head-related transfer functions (HRTFs), which capture directional acoustic cues, and visuals may be presented using a head-mounted display (HMD). For users of hearing devices such as hearing aids or cochlear implants, microphone placement may alter the binaural cues carried by the HRTF. Cues may also be distorted in presentations that combine HMD visuals with loudspeaker audio. This work seeks to understand these impacts by measuring and creating a database of HRTFs in the presence of hearing aids and HMDs. HRTFs were recorded within an anechoic chamber, using a standard manikin in a loudspeaker array located on the horizontal plane. Recordings were made with real sound sources of 5.625° resolution and virtual sources of 1° resolution. We will compare interaural time and level differences (ITDs and ILDs) from HRTFs measured through hearing-aid microphones with varied microphone placement (i.e., behind-the-ear and in-the-ear) and the presence versus absence of an HMD during the HRTF recording. Results will provide insights regarding HRTFs for individuals with hearing devices, as well as characterization of the HMD impact on VR-guided individual HRTF measurement.

HRTFs Measurement Based on Periodic Sequences Robust towards Nonlinearities in Automotive Audio.

The head related transfer functions (HRTFs) represent the acoustic path transfer functions between sound sources in 3D space and the listener's ear. They are used to create immersive audio scenarios or to subjectively evaluate sound systems according to a human-centric point of view. Cars are nowadays the most popular audio listening environment and the use of HRTFs in automotive audio has recently attracted the attention of researchers. In this context, the paper proposes a measurement method for HRTFs based on perfect or orthogonal periodic sequences. The proposed measurement method ensures robustness towards the nonlinearities that may affect the measurement system. The experimental results considering both an emulated scenario and real measurements in a controlled environment illustrate the effectiveness of the approach and compare the proposed method with other popular approaches.

Estimation of the Optimal Spherical Harmonics Order for the Interpolation of Head-Related Transfer Functions Sampled on Sparse Irregular Grids

Conventional individual head-related transfer function (HRTF) measurements are demanding in terms of measurement time and equipment. For more flexibility, free body movement (FBM) measurement systems provide an easy-to-use way to measure full-spherical HRTF datasets with less effort. However, having no fixed measurement installation implies that the HRTFs are not sampled on a predefined regular grid but rely on the individual movements of the subject. Furthermore, depending on the measurement effort, a rather small number of measurements can be expected, ranging, for example, from 50 to 150 sampling points. Spherical harmonics (SH) interpolation has been extensively studied recently as one method to obtain full-spherical datasets from such sparse measurements, but previous studies primarily focused on regular full-spherical sampling grids. For irregular grids, it remains unclear up to which spatial order meaningful SH coefficients can be calculated and how the resulting interpolation error compares to regular grids. This study investigates SH interpolation of selected irregular grids obtained from HRTF measurements with an FBM system. Intending to derive general constraints for SH interpolation of irregular grids, the study analyzes how the variation of the SH order affects the interpolation results. Moreover, the study demonstrates the importance of Tikhonov regularization for SH interpolation, which is popular for solving ill-posed numerical problems associated with such irregular grids. As a key result, the study shows that the optimal SH order that minimizes the interpolation error depends mainly on the grid and the regularization strength but is almost independent of the selected HRTF set. Based on these results, the study proposes to determine the optimal SH order by minimizing the interpolation error of a reference HRTF set sampled on the sparse and irregular FBM grid. Finally, the study verifies the proposed method for estimating the optimal SH order by comparing interpolation results of irregular and equivalent regular grids, showing that the differences are small when the SH interpolation is optimally parameterized.

Interaural time difference individualization in HRTF by scaling through anthropometric parameters

Head-related transfer function (HRTF) individualization can improve the perception of binaural sound. The interaural time difference (ITD) of the HRTF is a relevant cue for sound localization, especially in azimuth. Therefore, individualization of the ITD is likely to result in better sound spatial localization. A study of ITD has been conducted from a perceptual point of view using data from individual HRTF measurements and subjective perceptual tests. Two anthropometric dimensions have been demonstrated in relation to the ITD, predicting the subjective behavior of various subjects in a perceptual test. With this information, a method is proposed to individualize the ITD of a generic HRTF set by adapting it with a scale factor, which is obtained by a linear regression formula dependent on the two previous anthropometric dimensions. The method has been validated with both objective measures and another perceptual test. In addition, practical regression formula coefficients are provided for fitting the ITD of the generic HRTFs of the widely used Brüel & Kjær 4100 and Neumann KU100 binaural dummy heads.

Head-related transfer function measurements in a compartment fire.

The Personal Alert Safety System (PASS) is an alarm signal device carried by firefighters to help rescuers locate and extricate downed firefighters. A fire creates temperature gradients and inhomogeneous time-varying temperature, density, and flow fields that modify the acoustic properties of a room. To understand the effect of the fire on an alarm signal, experimental measurements of head-related transfer functions (HRTF) in a room with fire are presented in time and frequency domains. The results show that low-frequency (<1000 Hz) modes in the HRTF increase in frequency and higher-frequency modal structure weakens and becomes unstable in time. In the time domain, the time difference of arrival between the ears changes and becomes unstable over time. Both of these effects could impact alarm signal detection and localization. The receive level of narrowband tones is presented that shows that the fire makes the receive level of a source vary by > 10 dB. All of these effects could impact the detection and localization of the PASS alarm and have life safety consequences.

Compensating first reflections in non-anechoic head-related transfer function measurements

Personalized Head-Related Transfer Functions (HRTFs) are needed as part of the binaural sound individualization process in order to provide a high-quality immersive experience for a specific user. Signal processing methods for performing HRTF measurements in non-anechoic conditions are of high interest to avoid the complex and inconvenient access to anechoic facilities. Non-anechoic HRTF measurements capture the effect of room reflections, which should be correctly identified and eliminated to obtain HRTFs estimates comparable to ones acquired in an anechoic setup. This paper proposes a sub-band frequency-dependent processing method for reflection suppression in non-anechoic HRTF signals. Array processing techniques based on Plane Wave Decomposition (PWD) are adopted as an essential part of the solution for low frequency ranges, whereas the higher frequencies are easily handled by means of time-crop windowing methods. The formulation of the model, extraction of parameters and evaluation of the method are described in detail. In addition, a validation case study is presented showing the suppression of reflections from an HRTF measured in a real system. The results confirm that the method allows to obtain processed HRTFs comparable to those acquired in anechoic conditions.

The quantification of head-related transfer function’s dependency on anthropometric features

The work quantifies the anthropometric dependency of the head-related transfer functions(HRTFs). The human body modifies the soundwaves while traveling to the ear canal from different spatial locations, and the HRTF defines the transformation. The peaks and notches in the HRTF magnitude spectrum, generated by the complex asymmetrical shape of the outer ear (pinna), are essential for sound localization in the elevation plane. However, the anthropometric dependency of HRTF is not well quantified in the literature. The huge experimental cost of conventional HRTF measurement methods is a hurdle in these studies. To overcome this, distance-dependent HRTFs have been evaluated using the finite element-based computational tool on surface meshes of the human upper body with different pinnae. The size and interaural position of the pinna were altered, and various HRTF simulations were carried out in the study. The frequency shift of the spectral peaks and notches in the magnitude spectrum was examined to understand its anthropometric dependency. The dependency of HRTF on human anthropometric features was appraised in the proposed work. It can be beneficial in predicting personalized HRTF according to the size and interaural position of the subject’s pinna.

Head related transfer function measurements of common PPE

Due to COVID 19, personal protective equipment (PPE) is now used in everyday life. Such PPE affects communication and perception. This paper provides an overview of the impact of PPE on Head Related Transfer Functions (HRTF's). Spatial acoustic effects of common PPE on human hearing can be documented to improve and inform field worker safety and communication. After a general description of the measurement process and required tools, we focus on a few methods which contribute significantly to the accuracy and analysis of PPE-based HRTF data. The dedicated setup allows measuring a full 360 degree map in automated fashion. It includes a special ring setup with 25 speakers, and a precise turn table that is used to adjust the angle of the device under test with respect to the ring. Binaural measurements were performed on a set of common PPE items on a Head And Torso Simulator (HATS) system, including hard hats, safety glasses, hearing protection, and various face masks. An overview of the data is presented.

Cross-site investigation on head-related and headphone transfer functions: variabilities in relation to loudness balancing

Headphone transfer function (HpTF) and head-related transfer function (HRTF) measurements are crucial in acoustic science and in binaural virtual acoustic applications. Yet, their measurement set-up, procedure or post-processing is different for nearly every lab, especially for the HRTF measurements. To compare findings between different labs, these measurement deviations have to be quantified alongside with their influence on perceptual aspects. In the scope of a cross-site investigation on loudness balancing between headphone and loudspeaker listening, a set of HpTFs with three different headphones (open, closed, insert earphones) and HRTF close to the eardrum were measured in 14 participants travelling to two different measurement sites at Aachen and Oldenburg. Though set-ups for measuring the HRTF are very different between sites, the gathered HRTFs are quite consistent across them. For the measured HpTFs, across sites the open headphones consistently yield a slightly lower variability in the range from 70 to 5000 Hz than the closed one while the insert earphones exhibit much higher variabilities and a limited range of reproducible results. The difference in loudness balancing across labs could well be predicted by site-specific systematic differences in HpTFs with the exception of 1 kHz narrowband stimulus. This clearly indicates the limits in comparability of HpTFs and loudness balancing across labs and the importance of using headphones with high repeatability like the open ones used in this investigation.

Small footprint head-related transfer function measurement apparatus for binaural heads utilizing one loudspeaker

Apparatuses for measuring head-related transfer-functions (HRTFs) often require large anechoic spaces with one or more arcs of loudspeakers. A measurement setup to obtain the HRTF of a Brüel &amp; Kjær HATS 4100-D binaural head was designed and implemented that utilizes one loudspeaker in a 1309 ft3 anechoic space with 18 in. wedges. By rotating the HATS along two axes, the characterization of many look directions can be achieved. The HATS can be rotated about the axis through the center of the ears via a turntable, and the yaw of the HATS can be adjusted via mounting gear on custom framing. HRTF measurements were completed using both maximum-length sequence and sine sweep signals in order to compare the two techniques. Comparisons between the measured 4100-D HRTF and the HRTF of a similar B&amp;K binaural head will be discussed, as well as plans to use the 4100-D HRTF to compare binaural room impulse responses (RIRs) with spatial RIRs obtained with a spherical microphone array. [Work supported by a Graduate Assistance in Areas of National Need (GAANN) Fellowship.]

Low-Order Spherical Harmonic HRTF Restoration Using a Neural Network Approach

Spherical harmonic (SH) interpolation is a commonly used method to spatially up-sample sparse head related transfer function (HRTF) datasets to denser HRTF datasets. However, depending on the number of sparse HRTF measurements and SH order, this process can introduce distortions into high frequency representations of the HRTFs. This paper investigates whether it is possible to restore some of the distorted high frequency HRTF components using machine learning algorithms. A combination of convolutional auto-encoder (CAE) and denoising auto-encoder (DAE) models is proposed to restore the high frequency distortion in SH-interpolated HRTFs. Results were evaluated using both perceptual spectral difference (PSD) and localisation prediction models, both of which demonstrated significant improvement after the restoration process.

Measurement of Head-Related Transfer Functions: A Review

A head-related transfer function (HRTF) describes an acoustic transfer function between a point sound source in the free-field and a defined position in the listener’s ear canal, and plays an essential role in creating immersive virtual acoustic environments (VAEs) reproduced over headphones or loudspeakers. HRTFs are highly individual, and depend on directions and distances (near-field HRTFs). However, the measurement of high-density HRTF datasets is usually time-consuming, especially for human subjects. Over the years, various novel measurement setups and methods have been proposed for the fast acquisition of individual HRTFs while maintaining high measurement accuracy. This review paper provides an overview of various HRTF measurement systems and some insights into trends in individual HRTF measurements.

Pinna-related transfer functions and lossless wave equation using finite-difference methods: Validation with measurements.

Nowadays, wave-based simulations of head-related transfer functions (HRTFs) lack strong justifications to replace HRTF measurements. The main cause is the complex interactions between uncertainties and biases in both simulated and measured HRTFs. This paper deals with the validation of pinna-related high-frequency information in the ipsilateral directions-of-arrival, computed by lossless wave-based simulations with finite-difference models. A simpler yet related problem is given by the pinna-related transfer function (PRTF), which encodes the acoustical effects of only the external ear. Results stress that PRTF measurements are generally highly repeatable but not necessarily easily reproducible, leading to critical issues in terms of reliability for any ground truth condition. On the other hand, PRTF simulations exhibit an increasing uncertainty with frequency and grid-dependent frequency changes, which are here quantified analyzing the benefits in the use of a unique asymptotic solution. In this validation study, the employed finite-difference model accurately and reliably predict the PRTF magnitude mostly within ±1 dB up to ≈8 kHz and a space- and frequency-averaged spectral distortion within about 2 dB up to ≈ 18 kHz.

HRTF measurement by means of unsupervised head movements with respect to a single fixed speaker

In a standard state-of-the-art measurement the head-related transfer function (HRTF) is obtained in an anechoic room with an elaborate setup involving multiple calibrated loudspeakers. In search for a simplified method that would open up the possibility for an HRTF measurement in a home environment, it has been suggested that this setup could be replaced with one with a single, fixed loudspeaker. In such a setup, the subject samples different directions by moving the head with respect to this loudspeaker, while the head movements are tracked in some way. In this paper, the feasibility of such an approach is studied. To this end, the HRTF is measured in an unmodified (non-anechoic) room by means of a single external speaker and a high resolution head tracking system. The differences between the dynamically obtained HRTF and the standard static HRTF are investigated, and are shown to be mostly due to variable torso reflections.

Efficient Representation and Sparse Sampling of Head-Related Transfer Functions Using Phase-Correction Based on Ear Alignment

With the proliferation of high quality virtual reality systems, the demand for high fidelity spatial audio reproduction has grown. This requires individual head-related transfer functions (HRTFs) with high spatial resolution. Acquiring such HRTFs is not always possible, which motivates the need for sparsely sampled HRTFs. Additionally, real-time applications require compact representation of HRTFs. Recently, spherical-harmonics (SH) has been suggested for efficient interpolation and representation of HRTFs. However, representation of sparse HRTFs with a limited SH order may introduce spatial aliasing and truncation errors, which have a detrimental effect on the reproduced spatial audio. This is because the HRTF is inherently of a high spatial order. One approach to overcome this limitation is to pre-process the HRTF, with the aim of reducing its effective SH order. A recent study showed that order-reduction can be achieved by time-alignment of HRTFs, through numerical estimation of the time delays of the HRTFs. In this paper, a new method for pre-processing HRTFs in order to reduce their effective order is presented. The method uses phase-correction based on ear alignment, by exploiting the dual-centering nature of HRTF measurements. In contrast to time-alignment, the phase-correction is performed parametrically, making it more robust to measurement noise. The SH order reduction and ensuing interpolation errors due to sparse sampling were analyzed for these two methods. Results indicate significant reduction in the effective SH order, where only 100 measurements and order 6 are required to achieve a normalized mean square error below $-$ 10 dB compared to a fully-sampled, high-order HRTF.

On the Influence of Continuous Subject Rotation During High-Resolution Head-Related Transfer Function Measurements

In recent years, the required time for high resolution individual head-related transfer function (HRTF) measurements has been reduced by the use of microphone or loudspeaker arrays and with parallelization of measurement signals. While a short measurement time is beneficial during HRTF measurement of any resolution, it is essential for the acquisition of high resolution individual HRTF measurements since subjects cannot remain motionless over extended periods of time. This decrease in measurement time can be achieved by using continuous rotation during the measurement, instead of step-wise subject positioning. This paper examines the influence of such continuous measurement rotation with sine sweep measurements and the necessary subsequent post-processing. The goal is to identify a rotation speed, from a predefined set of speeds, that does not have an audible influence on the measured HRTF itself. To this end, a subjective and objective comparison between the two measurement modes is presented in this paper. Five HRTF measurements of an artificial head are acquired using different rotation speeds. They are compared objectively to a reference measurement of the same head performed with step-wise measurement rotation in the same measurement setup. A subjective listening experiment examines whether the found differences between the measurements do result in an audible difference. The objective evaluation showed expected trends regarding the dependency of the error on the measurement speed and is used to validate the used signal post-processing. The subjective evaluation showed that with a rotation of 3.8 $^\circ$ /s no audible differences to the reference are present.

Multiple Scattering Between Adjacent Sound Sources in Head-Related Transfer Function Measurement System

Multiple Scattering Between Adjacent Sound Sources in Head-Related Transfer Function Measurement System

Localization and externalization in binaural reproduction with sparse HRTF measurement grids

High-quality spatial sound reproduction is important for many applications of virtual and augmented reality. A key component in spatial audio reproduction is the head-related transfer function (HRTF). To achieve a realistic spatial audio experience, in terms of sound localization and externalization, high resolution individualized HRTFs are necessary. However, these are typically unavailable as they require specialized equipment and a large number of measurements, which motivates the use of sparsely measured HRTFs. Reducing the number of measurement points requires spatial interpolation, and may lead to spatial aliasing error. Previous studies suggested the use of spherical-harmonics (SH) decomposition for the interpolation. With a sparse grid, the SH representation is order-limited, leading to a constrained spatial resolution due to the truncation error. In this study, the effect of sparse measurement grids on the reproduced binaural signal is perceptually evaluated, through localization and externalization tests under varying conditions of aliasing and truncation. Preliminary results indicate relatively large effect of SH order on these attributes, while smaller effect is observed due to aliasing error.