5 papers · 1 filter
IS : Generic Impulsive--Stationary Sound Separation in Acoustic Scenes using Deep Filtering
Clémentine Berger, Paraskevas Stamatiadis, Roland Badeau +1
We are interested in audio systems capable of performing a differentiated processing of stationary backgrounds and isolated acoustic events within an acoustic scene, whether for ap…
TACO: Training-free Sound Prompted Segmentation via Semantically Constrained Audio-visual CO-factorization
Hugo Malard, Michel Olvera, Stephane Lathuiliere +1
Large-scale pre-trained audio and image models demonstrate an unprecedented degree of generalization, making them suitable for a wide range of applications. Here, we tackle the spe…
A Contrastive Self-Supervised Learning scheme for beat tracking amenable to few-shot learning
Antonin Gagnere, Geoffroy Peeters, Slim Essid
In this paper, we propose a novel Self-Supervised-Learning scheme to train rhythm analysis systems and instantiate it for few-shot beat tracking. Taking inspiration from the Contra…
An Eye for an Ear: Zero-shot Audio Description Leveraging an Image Captioner using Audiovisual Distribution Alignment
Hugo Malard, Michel Olvera, Stéphane Lathuiliere +1
Multimodal large language models have fueled progress in image captioning. These models, fine-tuned on vast image datasets, exhibit a deep understanding of semantic concepts. In th…
Less Forgetting for Better Generalization: Exploring Continual-learning Fine-tuning Methods for Speech Self-supervised Representations
Salah Zaiem, Titouan Parcollet, Slim Essid
Despite being trained on massive and diverse datasets, speech self-supervised encoders are generally used for downstream purposes as mere frozen feature extractors or model initial…