Results 11 to 20 of about 7,755 (225)
PRTFNet: HRTF Individualization for Accurate Spectral Cues Using a Compact PRTF
IEEE Access, 2023 Spatial audio rendering relies on accurate localization perception, which requires individual head-related transfer functions (HRTFs). Previous methods based on deep neural networks (DNNs) for predicting HRTF magnitude spectra from pinna images used HRTF
Byeong-Yun Ko +3 more
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Assessing HRTF preprocessing methods for Ambisonics rendering through perceptual models
Acta Acustica, 2022 Binaural rendering of Ambisonics signals is a common way to reproduce spatial audio content. Processing Ambisonics signals at low spatial orders is desirable in order to reduce complexity, although it may degrade the perceived quality, in part due to the
Engel Isaac +2 more
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EURASIP Journal on Audio, Speech, and Music Processing, 2022 One of the greatest challenges in the development of binaural machine audition systems is the disambiguation between front and back audio sources, particularly in complex spatial audio scenes.
Sławomir K. Zieliński +3 more
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CAAI Transactions on Intelligence Technology, 2022 Various time‐frequency (T‐F) masks are being applied to sound source localization tasks. Moreover, deep learning has dramatically advanced T‐F mask estimation. However, existing masks are usually designed for speech separation tasks and are suitable only
Hong Liu +4 more
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Applied Sciences, 2018 This paper proposes a personalized head-related transfer function (HRTF) estimation method based on deep neural networks by using anthropometric measurements and ear images. The proposed method consists of three sub-networks for representing personalized
Geon Woo Lee, Hong Kook Kim
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EURASIP Journal on Audio, Speech, and Music Processing, 2020 Binaural sound source localization is an important and widely used perceptually based method and it has been applied to machine learning studies by many researchers based on head-related transfer function (HRTF).
Jing Wang +4 more
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HRTF Individualization using Deep Learning
2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 2020 The research presented in this paper focuses on Head-Related Transfer Function (HRTF) individualization using deep learning techniques. HRTF individualization is paramount for accurate binaural rendering, which is used in XR technologies, tools for the ...
Riccardo Miccini, Simone Spagnol
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Hemoadsorption therapy for myoglobin removal in rhabdomyolysis: consensus of the hemoadsorption in rhabdomyolysis task force [PDF]
BMC NephrologyBackground Rhabdomyolysis describes a syndrome characterized by muscle necrosis and the subsequent release of creatine kinase and myoglobin into the circulation.
Lui Forni +18 more
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HRTF Individualization: A Survey [PDF]
arXiv.org, 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
Corentin Guezenoc, R. Séguier
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HRTF Upsampling With a Generative Adversarial Network Using a Gnomonic Equiangular Projection [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2023 An individualised head-related transfer function (HRTF) is very important for creating realistic virtual reality (VR) and augmented reality (AR) environments. However, acoustically measuring high-quality HRTFs requires expensive equipment and an acoustic
Aidan O. T. Hogg +5 more
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