7 papers
Mind the Microphone Gap: Benchmarking Array Upsampling Strategies for Latent Acoustic Mapping
Philipp Schmidt, Huw Cheston, Juan Azcarreta +3
Latent Acoustic Mapping (LAM) is a self-supervised learning method that generates high-resolution spherical acoustic maps from multichannel recordings without labelled data, matchi…
Clean2FX: Label-conditioned modeling for clean-to-effect guitar audio transformations
Oliverio Bombicci Pontelli, Iran R. Roman
We present Clean2FX, a study and demo of label-conditioned clean-to-effect transformation for electric guitar audio. Given a clean guitar input and a target effect label, the task…
EgoMAGIC- An Egocentric Video Field Medicine Dataset for Training Perception Algorithms
Brian VanVoorst, Nicholas Walczak, Christopher Gilleo +9
This paper introduces EgoMAGIC (Medical Assistance, Guidance, Instruction, and Correction), an egocentric medical activity dataset collected as part of DARPA's Perceptually-enabled…
Stereo Sound Event Localization and Detection with Onscreen/offscreen Classification
Kazuki Shimada, Archontis Politis, Iran R. Roman +10
This paper presents the objective, dataset, baseline, and metrics of Task 3 of the DCASE2025 Challenge on sound event localization and detection (SELD). In previous editions, the c…
Latent Acoustic Mapping for Direction of Arrival Estimation: A Self-Supervised Approach
Adrian S. Roman, Iran R. Roman, Juan P. Bello
Acoustic mapping techniques have long been used in spatial audio processing for direction of arrival estimation (DoAE). Traditional beamforming methods for acoustic mapping, while…
Spectrotemporal Modulation: Efficient and Interpretable Feature Representation for Classifying Speech, Music, and Environmental Sounds
Andrew Chang, Yike Li, Iran R. Roman +1
Audio DNNs have demonstrated impressive performance on various machine listening tasks; however, most of their representations are computationally costly and uninterpretable, leavi…