Translation-Equivariant Self-Supervised Learning for Pitch Estimation with Optimal Transport
Sound
2025-10-28 v1 Artificial Intelligence
Machine Learning
Audio and Speech Processing
Abstract
In this paper, we propose an Optimal Transport objective for learning one-dimensional translation-equivariant systems and demonstrate its applicability to single pitch estimation. Our method provides a theoretically grounded, more numerically stable, and simpler alternative for training state-of-the-art self-supervised pitch estimators.
Keywords
Cite
@article{arxiv.2508.01493,
title = {Translation-Equivariant Self-Supervised Learning for Pitch Estimation with Optimal Transport},
author = {Bernardo Torres and Alain Riou and Gaël Richard and Geoffroy Peeters},
journal= {arXiv preprint arXiv:2508.01493},
year = {2025}
}
Comments
Extended Abstracts for the Late-Breaking Demo Session of the 26th International Society for Music Information Retrieval Conference