arXiv:2510. 01891v2 Announce Type: replace-cross Abstract: Individual Head-Related Transfer Functions (HRTFs) are starting to be introduced in many commercial immersive audio applications and are crucial for realistic spatial audio rendering.
By Xuyi Hu, Jian Li, Shaojie Zhang, Stefan Goetz, Lorenzo Picinali, Ozgur B. Akan, Aidan O. T. Hogg
Sonic-AMG is a novel framework that generates human motion in real time from spatial audio, the first to do so in a streaming manner. It encodes acoustic content and body-relative source geometry as separate tokens, then uses a causal transformer with a flow head to produce continuous motion latents that a causal decoder turns into motion segments. The system introduces rehearsal training and spatial feedback to mitigate training‑inference mismatches, achieving state‑of‑the‑art FID and R‑precision on the SAM benchmark while enabling coherent, real‑time reactions to sound events and source locations.
By Jingcheng Ni, Zekun Li, Zhiyang Dou, Xiaoyan Cong, Ziyao Zeng, Hongyang Du, Randall Balestriero, Taku Komura, Srinath Sridhar
arXiv:2607. 04471v1 Announce Type: cross Abstract: Linear spatial filters (beamformers) enable robust, generalizable and interpretable speech enhancement with performance guarantees under ideal parameterization.
By Jakob Kienegger, Tal Peer, Sina Khanagha, Timo Gerkmann
arXiv:2511. 13487v3 Announce Type: replace-cross Abstract: This study presents a systematic evaluation of time-frequency feature design for binaural sound source localization (SSL), focusing on how feature selection influences model performance across diverse conditions.
By Davoud Shariat Panah, Alessandro Ragano, Dan Barry, Jan Skoglund, Andrew Hines
arXiv:2609.35839v1 Announce Type: cross
Abstract: Handclaps provide an equipment-free excitation for room acoustics, but their unknown and variable source waveform makes room impulse response (RIR) e...
By Shih-Yu Lai, Kyung Yun Lee, Nils Meyer-Kahlen, Eloi Moliner, Bing-Yu Chen, Vesa V\"alim\"aki
BinauralVAE is an open‑source pipeline that reconstructs spatial audio using various Variational Autoencoder architectures, including complex‑valued variants, to learn latent representations of binaural signals. The project builds on realistic acoustic data from a simulated robot navigating an environment, providing a foundation for audio‑centric world models. It aims to map the causal link between navigational actions and their acoustic outcomes, positioning sound as a complementary modality for spatial awareness.
By Luis Vitor Zerkowski, Luiz Velho