4 papers
BEST-RQ-2: Contextualize-Then-Predict, a Two-Step Approach for Self-Supervised Audio Representations
Ludovic K. Tuncay, Etienne Labbé, Thomas Pellegrini
Self-supervised learning enables audio representations that transfer across domains and tasks. We present BEST-RQ-2, an evolution of BEST-RQ that retains frozen randomprojection-ba…
Audio-JEPA: Joint-Embedding Predictive Architecture for Audio Representation Learning
Ludovic Tuncay, Etienne Labbé, Emmanouil Benetos +1
Building on the Joint-Embedding Predictive Architecture (JEPA) paradigm, a recent self-supervised learning framework that predicts latent representations of masked regions in high-…
Hierarchical Label Propagation: A Model-Size-Dependent Performance Booster for AudioSet Tagging
Ludovic Tuncay, Etienne Labbé, Thomas Pellegrini
AudioSet is one of the most used and largest datasets in audio tagging, containing about 2 million audio samples that are manually labeled with 527 event categories organized into…
Self-Supervised Models for Phoneme Recognition: Applications in Children's Speech for Reading Learning
Lucas Block Medin, Thomas Pellegrini, Lucile Gelin
Child speech recognition is still an underdeveloped area of research due to the lack of data (especially on non-English languages) and the specific difficulties of this task. Havin…