7 citations · 18 across the 13 of their papers we have counts for
8 papers · 2 filters
A Two-Step Approach for Narrowband Source Localization in Reverberant Rooms
Wei-Ting Lai, Lachlan Birnie, Thushara Abhayapala +3
This paper presents a two-step approach for narrowband source localization within reverberant rooms. The first step involves dereverberation by modeling the homogeneous component o…
An Active Noise Control System Based on Soundfield Interpolation Using a Physics-informed Neural Network
Yile Angela Zhang, Fei Ma, Thushara Abhayapala +2
Conventional multiple-point active noise control (ANC) systems require placing error microphones within the region of interest (ROI), inconveniencing users. This paper designs a fe…
Head-Related Transfer Function Interpolation with a Spherical CNN
Xingyu Chen, Fei Ma, Yile Zhang +2
Head-related transfer functions (HRTFs) are crucial for spatial soundfield reproduction in virtual reality applications. However, obtaining personalized, high-resolution HRTFs is a…
Circumvent spherical Bessel function nulls for open sphere microphone arrays with physics informed neural network
Fei Ma, Thushara D. Abhayapala, Prasanga N. Samarasinghe
Open sphere microphone arrays (OSMAs) are simple to design and do not introduce scattering fields, and thus can be advantageous than other arrays for implementing spatial acoustic…
Sound Field Estimation around a Rigid Sphere with Physics-informed Neural Network
Xingyu Chen, Fei Ma, Amy Bastine +2
Accurate estimation of the sound field around a rigid sphere necessitates adequate sampling on the sphere, which may not always be possible. To overcome this challenge, this paper…
Spatial Upsampling of Head-Related Transfer Functions Using a Physics-Informed Neural Network
Fei Ma, Thushara D. Abhayapala, Prasanga N. Samarasinghe +1
Head-related transfer function (HRTF) capture the information that a person uses to localize sound sources in space, and thus is crucial for creating personalized virtual acoustic…