From the 1 of 17 linked papers with an AI index.
17 papers
DiffAU: Diffusion-Based Ambisonics Upscaling
Amit Milstein, Nir Shlezinger, Boaz Rafaely
The paper introduces DiffAU, a diffusion‑model‑based method that upscales first‑order Ambisonics recordings to third‑order Ambisonics, improving spatial resolution of 3D audio.
AmbiDrop: Ambisonics-Based Array-Agnostic Neural Speech Enhancement
Michael Tatarjitzky, Vladimir Tourbabin, Boaz Rafaely
Multichannel Deep Neural Networks (DNNs) have significantly improved speech enhancement performance; however, they typically remain constrained by reliance on fixed microphone arra…
AmbiDrop: Array-Agnostic Speech Enhancement Using Ambisonics Encoding and Dropout-Based Learning
Michael Tatarjitzky, Boaz Rafaely
Multichannel speech enhancement leverages spatial cues to improve intelligibility and quality, but most learning-based methods rely on specific microphone array geometry, unable to…
Array-Aware Ambisonics and HRTF Encoding for Binaural Reproduction With Wearable Arrays
Yhonatan Gayer, Vladimir Tourbabin, Zamir Ben Hur +2
This work introduces a novel method for binaural reproduction from arbitrary microphone arrays, based on array-aware optimization of Ambisonics encoding through Head-Related Transf…
SpatialNet with Binaural Loss Function for Correcting Binaural Signal Matching Outputs under Head Rotations
Dor Shamay, Boaz Rafaely
Binaural reproduction is gaining increasing attention with the rise of devices such as virtual reality headsets, smart glasses, and head-tracked headphones. Achieving accurate bina…
SRP-PHAT-NET: A Reliability-Driven DNN for Reverberant Speaker Localization
Bar Shaybet, Vladimir Tourbabin, Boaz Rafaely
Accurate Direction-of-Arrival (DOA) estimation in reverberant environments remains a fundamental challenge for spatial audio applications. While deep learning methods have shown st…