22 citations · 93 across the 11 of their papers we have counts for
5 papers · 1 filter
A Prototypical Triplet Loss for Cover Detection
Guillaume Doras, Geoffroy Peeters
Automatic cover detection -- the task of finding in a audio dataset all covers of a query track -- has long been a challenging theoretical problem in MIR community. It also became…
Cover Detection using Dominant Melody Embeddings
Guillaume Doras, Geoffroy Peeters
Automatic cover detection -- the task of finding in an audio database all the covers of one or several query tracks -- has long been seen as a challenging theoretical problem in th…
Conditioned-U-Net: Introducing a Control Mechanism in the U-Net for Multiple Source Separations
Gabriel Meseguer-Brocal, Geoffroy Peeters
Data-driven models for audio source separation such as U-Net or Wave-U-Net are usually models dedicated to and specifically trained for a single task, e.g. a particular instrument…
DALI: a large Dataset of synchronized Audio, LyrIcs and notes, automatically created using teacher-student machine learning paradigm
Gabriel Meseguer-Brocal, Alice Cohen-Hadria, Geoffroy Peeters
The goal of this paper is twofold. First, we introduce DALI, a large and rich multimodal dataset containing 5358 audio tracks with their time-aligned vocal melody notes and lyrics…
Improving singing voice separation using Deep U-Net and Wave-U-Net with data augmentation
Alice Cohen-Hadria, Axel Roebel, Geoffroy Peeters
State-of-the-art singing voice separation is based on deep learning making use of CNN structures with skip connections (like U-net model, Wave-U-Net model, or MSDENSELSTM). A key t…