arXiv AI

Spectro-Temporal Interference Confounds Phase Encoding in Spatial Audio Foundation Models

arXiv:2606. 14820v1 Announce Type: cross Abstract: Recent spatial self supervised audio models achieve high performance on localization tasks, raising questions about their encoding of microsecond interaural phase fine structures.

arXiv Computation and Language
Sep 25

Spooftral: Can Voxtral Audio-Language Model Detect Speech Spoofing?

The paper investigates whether the Voxtral audio‑language model can detect speech spoofing. It shows that without task‑specific adaptation, the model’s language‑model layers prioritize semantic content, making spoof‑discriminative acoustic cues less separable. By applying lightweight weight‑decomposed low‑rank adaptation (DoRA), the authors create Spooftral, which achieves an equal error rate of 4.25% on the ASVspoof5 evaluation set.

By Avishai Weizman, Yehuda Ben-Shimol, Itshak Lapidot
arXiv Machine Learning
Aug 24

AudioWorldSim: Realistic Binaural Audio Datasets For World Models

AudioWorldSim is an open‑source platform that generates realistic binaural audio datasets for training and evaluating audio‑based machine learning models, especially world models. It extends Meta’s SoundSpaces 2.0 by automating random agent navigation and correcting continuous sound composition. The project is publicly available on GitHub to support reproducibility in research.

By Luis Vitor Zerkowski, Luiz Velho