Results 111 to 120 of about 4,753 (195)

Cross-Dataset Head-Related Transfer Function Harmonization Based on Perceptually Relevant Loss Function

open access: yesIEEE Open Journal of Signal Processing
Head-Related Transfer Functions (HRTFs) play a vital role in binaural spatial audio rendering. With the release of numerous HRTF datasets in recent years, abundant data has become available to support HRTF-related research based on deep learning. However,
Jiale Zhao, Dingding Yao, Junfeng Li
doaj   +1 more source

Design and preliminary tests of a blade tip air mass injection system for vortex modification and possible noise reduction on a full-scale helicopter rotor [PDF]

open access: yes
Full-scale tests were conducted on the Langley helicopter rotor test facility as part of a study to evaluate the effectiveness of a turbulent blade tip air mass injection system in alleviating the impulsive noise (blade slap) caused by blade-vortex ...
Balcerak, J. C.   +3 more
core   +1 more source

Hiniennekadur HRTF: stad an arzh

open access: yes, 2018
The individuality of head-related transfer functions (HRTFs) is a key issue for binaural synthesis. While, over the years, a lot of work has been accomplished to propose end-user-friendly solutions to HRTF personalization, it remains a challenge. In this article we establish a state-of-the-art of that work.
Guezenoc, Corentin, Seguier, Renaud
openaire   +1 more source

Conversion of stereo recording to 5.1 format using head-related transfer functions

open access: yesArchives of Acoustics, 2014
The paper presents the conversion of stereo recordings into multi-channel format 5.1 by means of the HRTF filtering. An algorithm of additional channels preparation (a central one and two surround ones) using various filters created on the base of HRTF ...
Paweł HEN   +2 more
doaj  

Towards Perception-Informed Latent HRTF Representations

open access: yes2025 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)
Personalized head-related transfer functions (HRTFs) are essential for ensuring a realistic auditory experience over headphones, because they take into account individual anatomical differences that affect listening. Most machine learning approaches to HRTF personalization rely on a learned low-dimensional latent space to generate or select custom ...
Zhang, You   +5 more
openaire   +2 more sources

HRTF Sound Localization

open access: yes, 2011
Rothbucher, Martin   +4 more
openaire   +4 more sources

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