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HRTF Upsampling Across Varying Measurement Configurations with Geometry-Aware Query-Conditioned Aggregation
Xingyu Chen, Hanwen Bi, Sipei Zhao +3
Personalized head-related transfer functions (HRTFs) are essential for spatial audio rendering, but densely measuring an individual's HRTFs is costly and time-consuming. HRTF upsam…
Exploring Frequency-Domain Feature Modeling for HRTF Magnitude Upsampling
Xingyu Chen, Hanwen Bi, Fei Ma +3
Accurate upsampling of Head-Related Transfer Functions (HRTFs) from sparse measurements is crucial for personalized spatial audio rendering. Traditional interpolation methods, such…
Permutation-Invariant Physics-Informed Neural Network for Region-to-Region Sound Field Reconstruction
Xingyu Chen, Sipei Zhao, Fei Ma +2
Most existing sound field reconstruction methods target point-to-region reconstruction, interpolating the Acoustic Transfer Functions (ATFs) between a fixed-position sound source a…
A circular microphone array with virtual microphones based on acoustics-informed neural networks
Sipei Zhao, Fei Ma
Acoustic beamforming aims to focus acoustic signals to a specific direction and suppress undesirable interferences from other directions. Despite its flexibility and steerability,…
Sound Field Reconstruction Using a Compact Acoustics-informed Neural Network
Fei Ma, Sipei Zhao, Ian S. Burnett
Sound field reconstruction (SFR) augments the information of a sound field captured by a microphone array. Conventional SFR methods using basis function decomposition are straightf…