A mixed-order modeling approach for head-related transfer function in the spherical harmonic domain

2021 ◽  
Vol 176 ◽  
pp. 107828
Author(s):  
Junfeng Li ◽  
Biao Wu ◽  
Dingding Yao ◽  
Yonghong Yan
Keyword(s):  
Transfer Function ◽  
Spherical Harmonic ◽  
Modeling Approach ◽  
Mixed Order ◽  
Head Related Transfer Function

scholarly journals Speech intelligibility with various head-related transfer functions: A computational modeling approach

2020 ◽  
Author(s):  
Axel Ahrens ◽  
Maria Cuevas-Rodriguez ◽  
W. Owen Brimijoin
Keyword(s):  
Transfer Function ◽  
Computational Modeling ◽  
Speech Intelligibility ◽  
Transfer Functions ◽  
Spatial Separation ◽  
Spatial Position ◽  
Auditory Model ◽  
Modeling Approach ◽  
Head Related Transfer Function

AbstractSpeech intelligibility is known to be affected by the relative spatial position between target and interferers. The benefit of a spatial separation is, along with other factors, related to the head-related transfer function (HRTF). The HRTF is individually different and thus, the cues that improve speech intelligibility might also be different. In the current study an auditory model was employed to predict speech intelligibility with a variety of HRTFs. The predicted speech intelligibility was found to vary across HRTFs. Thus, individual listeners might have different access to cues that are important for speech intelligibility.

scholarly journals Spatial Unmasking Effect on Speech Reception Threshold in the Median Plane

2020 ◽  
Vol 10 (15) ◽  
pp. 5257
Author(s):  
Nathan Berwick ◽  
Hyunkook Lee
Keyword(s):  
Transfer Function ◽  
Input Signal ◽  
Function Analysis ◽  
Median Plane ◽  
Speech Reception ◽  
Transfer Function Analysis ◽  
Spatial Unmasking ◽  
Head Related Transfer Function ◽  
Speech Reception Thresholds ◽  
Energy Weighting

This study examined whether the spatial unmasking effect operates on speech reception thresholds (SRTs) in the median plane. SRTs were measured using an adaptive staircase procedure, with target speech sentences and speech-shaped noise maskers presented via loudspeakers at −30°, 0°, 30°, 60° and 90°. Results indicated a significant median plane spatial unmasking effect, with the largest SRT gain obtained for the −30° elevation of the masker. Head-related transfer function analysis suggests that the result is associated with the energy weighting of the ear-input signal of the masker at upper-mid frequencies relative to the maskee.

Head-related transfer function database and its analyses

2007 ◽  
Vol 50 (3) ◽  
pp. 267-280 ◽  
Author(s):  
BoSun Xie ◽  
XiaoLi Zhong ◽  
Dan Rao ◽  
ZhiQiang Liang
Keyword(s):  
Transfer Function ◽  
Head Related Transfer Function

Subjective Evaluation of Three Headphone-Based Virtual Sound Source Positioning Methods Including Differential Head-Related Transfer Function

2016 ◽  
Vol 41 (3) ◽  
pp. 437-447
Author(s):  
Dominik Storek ◽  
Frantisek Rund ◽  
Petr Marsalek
Keyword(s):  
Transfer Function ◽  
Sound Source ◽  
Subjective Evaluation ◽  
Sound Localisation ◽  
Signal Features ◽  
Listening Tests ◽  
Positioning Method ◽  
Head Related Transfer Function ◽  
Positioning Algorithm ◽  
Source Positioning

Abstract This paper analyses the performance of Differential Head-Related Transfer Function (DHRTF), an alternative transfer function for headphone-based virtual sound source positioning within a horizontal plane. This experimental one-channel function is used to reduce processing and avoid timbre affection while preserving signal features important for sound localisation. The use of positioning algorithm employing the DHRTF is compared to two other common positioning methods: amplitude panning and HRTF processing. Results of theoretical comparison and quality assessment of the methods by subjective listening tests are presented. The tests focus on distinctive aspects of the positioning methods: spatial impression, timbre affection, and loudness fluctuations. The results show that the DHRTF positioning method is applicable with very promising performance; it avoids perceptible channel coloration that occurs within the HRTF method, and it delivers spatial impression more successfully than the simple amplitude panning method.

scholarly journals A framework for designing head-related transfer function distance metrics that capture localization perception

2021 ◽  
Vol 1 (4) ◽  
pp. 044401
Author(s):  
Ishwarya Ananthabhotla ◽  
Vamsi Krishna Ithapu ◽  
W. Owen Brimijoin
Keyword(s):  
Transfer Function ◽  
Distance Metrics ◽  
Head Related Transfer Function

scholarly journals Low-order Spherical Harmonic HRTF Restoration using a Neural Network Approach

2020 ◽  
Author(s):  
Benjamin Tsui ◽  
William A. P. Smith ◽  
Gavin Kearney
Keyword(s):  
Neural Network ◽  
Spherical Harmonic ◽  
High Frequency ◽  
Prediction Models ◽  
Machine Learning Algorithms ◽  
Network Approach ◽  
Spectral Difference ◽  
Neural Network Approach ◽  
Frequency Representation ◽  
Head Related Transfer Function

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 in high frequency representation 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 are evaluated using both Perceptual Spectral Difference (PSD) and localisation prediction models, both of which demonstrate significant improvement after the restoration process.

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