collaborators

5 papers

cs.SD2026

The Costs of Reproducibility in Music Separation Research: a Replication of Band-Split RNN

Paul Magron, Romain Serizel, Constance Douwes

Music source separation is the task of isolating the instrumental tracks from a music song. Despite its spectacular recent progress, the trend towards more complex architectures an…

cs.SD2024

Energy Consumption Trends in Sound Event Detection Systems

Constance Douwes, Romain Serizel

Deep learning systems have become increasingly energy- and computation-intensive, raising concerns about their environmental impact. As organizers of the Detection and Classificati…

cs.LG2024

Normalizing Energy Consumption for Hardware-Independent Evaluation

Constance Douwes, Romain Serizel

The increasing use of machine learning (ML) models in signal processing has raised concerns about their environmental impact, particularly during resource-intensive training phases…

cs.LG2024

From Computation to Consumption: Exploring the Compute-Energy Link for Training and Testing Neural Networks for SED Systems

Constance Douwes, Romain Serizel

The massive use of machine learning models, particularly neural networks, has raised serious concerns about their environmental impact. Indeed, over the last few years we have seen…

eess.AS2024

DCASE 2024 Task 4: Sound Event Detection with Heterogeneous Data and Missing Labels

Samuele Cornell, Janek Ebbers, Constance Douwes +4

The Detection and Classification of Acoustic Scenes and Events Challenge Task 4 aims to advance sound event detection (SED) systems in domestic environments by leveraging training…