A high voltage damped oscillating wave generator

Head-related transfer function (HRTF) interpolation plays an important role for implementation of 3D sound system because it can not only reduce the number of measurements for HRTFs, but also reduce the data of HRTFs for seamless binaural synthesis. This paper addresses the problem of accurately realizing the interpolation of HRTF for synthesis of virtual auditory space, and proposes a HRTF interpolation method based on principal component analysis. Firstly, the HRTF is decomposed into principal components and corresponding principal component weights, where principal components are direction-independent and principal component weights are direction- dependent; then the directional variation of the principal component weight is multivariate polynomial fitted with a bivariate function of two spatial angulus (azimuth and elevation). Moreover, a sphere- partitioning optimization scheme is employed to improve the approximation precision. Experiment results demonstrate that HRTFs in the entire sphere surface can be interpolated by the proposed method with small distortion, and the proposed method performs better than conventional methods. Therefore the proposed method gives a promising way for HRTF interpolation.

Efficient prediction of individual head-related transfer functions based on 3D meshes

Head-related transfer function (HRTF) plays an important role in the construction of 3D auditory display. This paper presents an individual HRTF modeling method using deep neural networks based on spatial principal component analysis. The HRTFs are represented by a small set of spatial principal components combined with frequency and individual-dependent weights. By estimating the spatial principal components using deep neural networks and mapping the corresponding weights to a quantity of anthropometric parameters, we predict individual HRTFs in arbitrary spatial directions. The objective and subjective experiments evaluate the HRTFs generated by the proposed method, the principal component analysis (PCA) method, and the generic method. The results show that the HRTFs generated by the proposed method and PCA method perform better than the generic method. For most frequencies the spectral distortion of the proposed method is significantly smaller than the PCA method in the high frequencies but significantly larger in the low frequencies. The evaluation of the localization model shows the PCA method is better than the proposed method. The subjective localization experiments show that the PCA and the proposed methods have similar performances in most conditions. Both the objective and subjective experiments show that the proposed method can predict HRTFs in arbitrary spatial directions.

Toward orthogonal non-individualised head-related transfer functions for forward and backward directional sound: cluster analysis and an experimental study

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.

The techniques of an efficient 3-D sound system based on the psychoacoustics of spatial hearing with multimedia or virtual reality have been developed by many researchers. In this paper, we propose an idea for an improved 3-D sound system using conventional stereo headphones to obtain a better sound diffusion from the mono-sound recorded in an anechoic chamber. We use the HRTF (Head Related Transfer Function) for the sound localization and the wavelet filter bank with time delay for the sound diffusion. We investigate the effects of the 3-D sound depending on the length of time delay at the lowest frequency band. Also the correlation coefficient of the signals between the left channel and the right channel is measured to identify the sound diffusion.

3-dimensional sound field with high accuracy is an important topic for MR (Mixed Reality) to create the high immersion sense. HRTF (Head-Related Transfer Function) can achieve 3-dimensional sound field, whereas the measurement of the HRTF for each person is difficult because the measurement of the HRTF requires the expensive equipment and environment. In this paper, we propose a method to design HRTF by piecing several HRTFs selected from a large database of HRTFs. As a result of evaluation experiments, we confirmed that the proposed method can design the useful HRTF.

While various methods for sound source localization have been developed, most of them utilize on the time difference of arrival (TDOA) between microphones or the measured head related transfer functions (HRTF). In case of a real robot implementation, the former has a merit of light computation load to estimate the sound direction but can not consider the effect of platform on TDOAs, while the latter can, because characteristics of robot platform are included in HRTF. However, the latter needs large resources for the HRTF database of a specific robot platform. We propose the compensation method which has the light computation load while the effect of platform on TDOA can be taken into account. The proposed method is used with spherical head related transfer function (SHRTF) on the assumption that robot platform, for example a robot head, installed microphones can be modeled to a sphere. We verify that the proposed method decreases the estimation error caused by the robot platform through the simulation.

The Head Related Transfer Function (HRTF) means a process related to acoustic transmission from 3d space to the listener`s ear. In other words, it contains the information that human can perceive locations of sound sources. So, we make virtual 3d sound using HRTF, despite it doesn`t actually exist. But, it can deteriorate some three-dimensional effect by the confusion between front and back directions due to the non-individual HRTF depending on each listener. In this paper, we proposed the new algorithm to reduce the confusion of sound image localization using human`s acoustic characteristics. The frequency spectrum and global masking threshold of 3d sounds using HRTF are used to calculate the psychoacoustical differences among each directions. And perceptible cues in each critical band are boosted to create effective 3d sound. As a result, we can make the improved 3d sound, and the performances are much better than conventional methods.

In this article, a modified fractional internal model control (IMC) filter structure is proposed to design a fractional filter Proportional-Integral-Derivative (FFPID) controller for improved disturbance rejection of second order plus time delay (SOPTD) processes. The proposed method aims at improving the disturbance rejection of slow chemical processes as the tuning rules for such processes are limited. The present design also considers the higher order approximation for time delay as it gives improved response for higher order processes. There is an additional tuning parameter in the proposed IMC filter apart from the conventional IMC filter time constant, which is tuned according to the derived formula. The additional adjustable parameter achieves the disturbance rejection and the closed loop stability. The simulation results have been performed for the same degree of robustness (maximum sensitivity, Ms) for a fair comparison. The results show an improved disturbance rejection for lag dominant and delay significant SOPTD processes with the proposed controllers designed using higher order Pade’s approximation of time delay than the proposed method using first order approximation and the conventional method. The closed loop robust performance is observed for perturbations in the process parameters and the performance is also observed for noise in the measurement. The robust stability analysis is carried out using sensitivity functions. In addition, the Ms range is also identified over which the system gives robust performance for the controllers designed using higher order pade’s approximation of time delay compared to conventional method.

We investigated the azimuth angle characteristics of head related transfer function (HRTF) at very high frequency region using two kinds of head and torso simulators (HATS). In the measurement of hearing thresholds, there are two ways using a headphone or a loudspeaker. In general, it will be carried out using a loudspeaker because sound pressure calibration and measurement are simple. However, the hearing threshold which measured using a loudspeaker at very high frequency region may contain some errors because sound pressure level (SPL) reaching the ear are seriously affected by a small movement of the head. Also, the SPL near the pinna seriously depends on both shapes of a pinna and a head because excess attenuation by diffraction of VHF sound is very large. To provide assurance for the accuracy measurement of hearing threshold, it is important to make clear the relationship between the SPL and shape of head and/or ear. In this paper, we reported the HRTFs calculated from the SPLs measured at three different positions of left ear - a tragus, an auricle and an eardrum and discussed the influence of head and/or ear of HATS from the azimuth angle characteristics of these HRTFs.

As an alternative to traditional artificial heads, it is possible to synthesize individual head-related transfer functions (HRTFs) using a so-called virtual artificial head (VAH), consisting of a microphone array with an appropriate topology and filter coefficients optimized using a narrowband least squares cost function. The resulting spatial directivity pattern of such a VAH is known to be sensitive to small deviations of the assumed microphone characteristics, e.g., gain, phase and/or the positions of the microphones. In many beamformer design procedures, this sensitivity is reduced by imposing a white noise gain (WNG) constraint on the filter coefficients for a single desired look direction. In this paper, this constraint is shown to be inappropriate for regularizing the HRTF synthesis with multiple desired directions and three alternative different regularization approaches are proposed and evaluated. In the first approach, the measured deviations of the microphone characteristics are taken into account in the filter design. In the second approach, the filter coefficients are regularized using the mean WNG for all directions. The third approach additionally takes into account several frequency bins into both the optimization and the regularization. The different proposed regularization approaches are compared using analytic and measured transfer functions, including random deviations. Experimental results show that the approach using multiple frequency bands mimicking the spectral resolution of the human auditory system yields the best robustness among the considered regularization approaches.

Common-acoustic-poles/zeros (CAPZ) approximation is a more efficient way to model head-related transfer functions (HRTFs). In CAPZ approximation, a group of HRTFs can share a set of poles but use their own zeros. Previous CAPZ works, such as the Prony, Shanks and iterative prefiltering methods, were all based on the linearized least-square criterion. A new state-space approach, jointly balanced model truncation, is proposed by using singular value decomposition of a joint Hankel matrix. The proposed approach can choose the suitable order of IIR filters for HRTFs approximation according to the distribution of singular values but previous works can not. The proposed method is also modified to permit different orders for the poles and zeros. Computer simulations of these approaches are included for comparison.

In machine sound localization, convenient and effective estimation modes are required. A dummy head with certain head related transfer function (HRTF) can be introduced to sound localization instead of the conventional microphone array or other sensor systems. Since the spectrum of HRTF varies with the sound source direction, a sound localization method based on spectral cues is presented. By simplifying the direction estimation process of human spatial hearing, the directional information is extracted from the spectrum of HRTF and is multi coded in parallel with a feed forward neural network. Then the multi coded directional information is weighted to estimate the sound position. Simulations show that the proposed method is effective.

3D sounds systems are not new in multimedia world. A normal sound system can generate 3D sounds. When these systems are integrated with Virtual Reality (VR), or Augmented Reality (AR) where the image and sound both are dependent on the position of viewer, they are unable to generate 3D sound, because such systems are based on the body position. The paper proposes a head tracking based 3D sound system that utilizes Microsoft Kinect for head tracking, and Head Related Transfer Function (HRTF) for 3D sound generation. Initial results show promising future of the proposed technique for 3D sound generation.