1 citations · 1 across the 4 of their papers we have counts for
11 papers
Twenty-Five Years of MIR Research: Achievements, Practices, Evaluations, and Future Challenges
Geoffroy Peeters, Zafar Rafii, Magdalena Fuentes +4
In this paper, we trace the evolution of Music Information Retrieval (MIR) over the past 25 years. While MIR gathers all kinds of research related to music informatics, a large par…
Controlling Contrastive Self-Supervised Learning with Knowledge-Driven Multiple Hypothesis: Application to Beat Tracking
Antonin Gagnere, Slim Essid, Geoffroy Peeters
Ambiguities in data and problem constraints can lead to diverse, equally plausible outcomes for a machine learning task. In beat and downbeat tracking, for instance, different list…
MATPAC++: Enhanced Masked Latent Prediction for Self-Supervised Audio Representation Learning
Aurian Quelennec, Pierre Chouteau, Geoffroy Peeters +1
Masked latent prediction has emerged as a leading paradigm in self-supervised learning (SSL), especially for general audio and music representation learning. While recent methods h…
Translation-Equivariant Self-Supervised Learning for Pitch Estimation with Optimal Transport
Bernardo Torres, Alain Riou, Gaël Richard +1
In this paper, we propose an Optimal Transport objective for learning one-dimensional translation-equivariant systems and demonstrate its applicability to single pitch estimation.…
PESTO: Real-Time Pitch Estimation with Self-supervised Transposition-equivariant Objective
Alain Riou, Bernardo Torres, Ben Hayes +4
In this paper, we introduce PESTO, a self-supervised learning approach for single-pitch estimation using a Siamese architecture. Our model processes individual frames of a Variable…
Episode-specific Fine-tuning for Metric-based Few-shot Learners with Optimization-based Training
Xuanyu Zhuang, Geoffroy Peeters, Gaël Richard
In few-shot classification tasks (so-called episodes), a small set of labeled support samples is provided during inference to aid the classification of unlabeled query samples. Met…