3 papers
cs.SD2026
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…
cs.SD2025
Deconstructing Jazz Piano Style Using Machine Learning
Huw Cheston, Reuben Bance, Peter M. C. Harrison
Artistic style has been studied for centuries, and recent advances in machine learning create new possibilities for understanding it computationally. However, ensuring that machine…
cs.SD2025
Automatic Identification of Samples in Hip-Hop Music via Multi-Loss Training and an Artificial Dataset
Huw Cheston, Jan Van Balen, Simon Durand
Sampling, the practice of reusing recorded music or sounds from another source in a new work, is common in popular music genres like hip-hop and rap. Numerous services have emerged…