12 papers
Probing Spatial Structure in Pretrained Audio Representations
Chuyang Chen, Sivan Ding, Adrian S. Roman +1
Pretrained spatial audio encoders are increasingly used as general-purpose representations for perceptual tasks, yet their spatial encoding capabilities remain poorly understood. W…
Sensitivity Analysis of Generative Spatial Audio Metrics: A Study on Responsiveness, Smoothness, and Symmetry
Purnima Kamath, Adrian S. Roman, Koichi Saito +2
Evaluating generative spatial audio for First-Order Ambisonics (FOA) remains challenging due to a limited understanding of how metrics respond to changes in spatial parameters such…
Evaluating Compositional Structure in Audio Representations
Chuyang Chen, Bea Steers, Brian McFee +1
We propose a benchmark for evaluating compositionality in audio representations. Audio compositionality refers to representing sound scenes in terms of constituent sources and attr…
Latent Multi-view Learning for Robust Environmental Sound Representations
Sivan Ding, Julia Wilkins, Magdalena Fuentes +1
Self-supervised learning (SSL) approaches, such as contrastive and generative methods, have advanced environmental sound representation learning using unlabeled data. However, how…
Controllable Embedding Transformation for Mood-Guided Music Retrieval
Julia Wilkins, Jaehun Kim, Matthew E. P. Davies +2
Music representations are the backbone of modern recommendation systems, powering playlist generation, similarity search, and personalized discovery. Yet most embeddings offer litt…
Balancing Information Preservation and Disentanglement in Self-Supervised Music Representation Learning
Julia Wilkins, Sivan Ding, Magdalena Fuentes +1
Recent advances in self-supervised learning (SSL) methods offer a range of strategies for capturing useful representations from music audio without the need for labeled data. While…
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…
Self-Supervised Multi-View Learning for Disentangled Music Audio Representations
Julia Wilkins, Sivan Ding, Magdalena Fuentes +1
Self-supervised learning (SSL) offers a powerful way to learn robust, generalizable representations without labeled data. In music, where labeled data is scarce, existing SSL metho…
HuBar: A Visual Analytics Tool to Explore Human Behaviour based on fNIRS in AR guidance systems
Sonia Castelo, Joao Rulff, Parikshit Solunke +11
The concept of an intelligent augmented reality (AR) assistant has significant, wide-ranging applications, with potential uses in medicine, military, and mechanics domains. Such an…
Spatial Scaper: A Library to Simulate and Augment Soundscapes for Sound Event Localization and Detection in Realistic Rooms
Iran R. Roman, Christopher Ick, Sivan Ding +3
Sound event localization and detection (SELD) is an important task in machine listening. Major advancements rely on simulated data with sound events in specific rooms and strong sp…
Robust DOA estimation using deep acoustic imaging
Adrian S. Roman, Iran R. Roman, Juan P. Bello
Direction of arrival estimation (DoAE) aims at tracking a sound in azimuth and elevation. Recent advancements include data-driven models with inputs derived from ambisonics intensi…
Sound Source Distance Estimation in Diverse and Dynamic Acoustic Conditions
Saksham Singh Kushwaha, Iran R. Roman, Magdalena Fuentes +1
Localizing a moving sound source in the real world involves determining its direction-of-arrival (DOA) and distance relative to a microphone. Advancements in DOA estimation have be…