5 papers
Array-Agnostic High-Order Ambisonics Encoding via Diffusion Posterior Sampling
Amit Milstein, Nir Shlezinger, Boaz Rafaely
Ambisonics provides a device-independent representation of three-dimensional sound fields; however, extracting these coefficients from practical microphone array recordings remains…
Generative Learning for Ambisonic Upscaling
Amit Milstein, Nir Shlezinger, Boaz Rafaely
Ambisonics Upscaling (AU) aims to enhance the spatial resolution of sound fields by estimating high-order Ambisonics (HOA) components from low-order observations. While deep learni…
Array-Agnostic Ambisonics Encoding via Diffusion Posterior Sampling
Amit Milstein, Nir Shlezinger, Boaz Rafaely
Spatial audio enhances user immersion by reproducing 3D sound fields, with Ambisonics being a widely adopted representation. While Ambisonics is theoretically independent of the re…
DiffAU: Diffusion-Based Ambisonics Upscaling
Amit Milstein, Nir Shlezinger, Boaz Rafaely
Spatial audio enhances immersion by reproducing 3D sound fields, with Ambisonics offering a scalable format for this purpose. While first-order Ambisonics (FOA) notably facilitates…
Deep Unfolding with Approximated Computations for Rapid Optimization
Dvir Avrahami, Amit Milstein, Caroline Chaux +2
Optimization-based solvers play a central role in a wide range of signal processing and communication tasks. However, their applicability in latency-sensitive systems is limited by…