AI & ML
ARPEGE: Dataset and Methods to Estimate Acoustic and Geometric Parameters of Rooms from Sound
arXiv cs.SD0 views
arXiv:2610.41543v1 Announce Type: new Abstract: Can one hear the walls of a room? To foster audio signal processing research around this question we release ARPEGE, a dataset containing hundreds of ambisonic spherical-array room impulse responses recorded in 6 empty rooms, annotated by the relative positions of sources, microphones and all acoustic reflectors. The dataset includes multiple room sizes, surface materials, orientations and distances, as well as recordings of human speakers and handclaps. Two state-of-the-art methods on image source localization and blind room parameter estimation are demonstrated on the data. Initial code for re-simulating the measured room impulse responses is provided, a longer term goal being to digitally twin the dataset.
Source:https://arxiv.org/abs/2610.41543PreviousScalable Audio-LLM System for Speech MOS Evaluation: A Diagnostic Case Study and Adaptation RoadmapNextSelf-Localization of Distributed Microphone Arrays Using One Source and Acoustic Reflections
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