Abstract
Head-related transfer function (HRTF), which varies across individuals at the same direction, has grabbed widespread attention in the field of acoustics and been used in many scenarios. In order to in-depth investigate the performance of individualized HRTFs on perceiving the spatialization cues, this study presents an integrated algorithm to obtain individualized HRTFs, and explores the advancement of such individualized HRTFs in perceiving the spatialization cues through two different binaural experiments. An integrated method for HRTF individualization on the use of Principle Component Analysis (PCA), Multiple Linear Regression (MLR) and Partial Least Square Regression (PLSR) was presented first. The objective evaluation was then made to verify the algorithmic effectiveness of that method. Next, two subjective experiments were conducted to explore the advancement of individualized HRTFs in perceiving the spatialization cues. One was auditory directional discrimination degree based on semantic differential method, in which the azimuth information of sound sources was told to the listeners before listening. The other was auditory localization, in which the azimuth information was not told to the listeners before listening. The corresponding statistical analyses for the subjective experimental results were made. All the experimental results support that individualized HRTFs obtained from the presented method achieve a preferable performance in perceiving the spatialization cues.
Highlights
Auditory sensing is essential for human beings to perceive the three-dimensional (3D) environment.The human hearing system can localize sound sources by using of the spatialization cues of the sources, for which head-related transfer functions (HRTFs) and the corresponding impulse responses play a vital role
All the experimental results support that individualized HRTFs obtained from the presented method achieve a preferable performance in perceiving the spatialization cues
To synthesize HRTFs for any listener, we present an integrated algorithm combing the method of correlation analysis, principle component analysis (PCA), multiple linear regression (MLR)
Summary
The human hearing system can localize sound sources by using of the spatialization cues of the sources, for which head-related transfer functions (HRTFs) and the corresponding impulse responses (head-related impulse responses, HRIRs) play a vital role. HRTF is the transfer function of a linear system describing the filtering effect of the pinna, head and torso of a listener as a sound propagates from the source to the ear drum in free space [1]. HRTFs are highly individualized, as the aforementioned anthropometric features are listener-dependent. HRTFs are defined as the ratio of the Fourier transform of the signal at the listener’s eardrum to that at the center of the listener’s head with the listener absent [1]. Obtaining accurate binaural HRTFs is of great significance in generating
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