no code implementations • 1 Mar 2024 • Rémi Mignot, Geoffroy Peeters
Finally, anchoring the analysis times on local maxima of a selected onset function, an approximative hashing is done to provide a better tolerance to bit corruptions, and in the same time to make easier the scaling of the method.
1 code implementation • 22 Dec 2023 • Bernardo Torres, Geoffroy Peeters, Gaël Richard
In neural audio signal processing, pitch conditioning has been used to enhance the performance of synthesizers.
no code implementations • 21 Dec 2023 • Aurian Quelennec, Michel Olvera, Geoffroy Peeters, Slim Essid
Choosing the best one for a set of tasks is the subject of many recent publications.
1 code implementation • 5 Sep 2023 • Geoffroy Peeters
Music Structure Analysis (MSA) is the task aiming at identifying musical segments that compose a music track and possibly label them based on their similarity.
no code implementations • 5 Sep 2023 • Alain Riou, Stefan Lattner, Gaëtan Hadjeres, Geoffroy Peeters
In this paper, we address the problem of pitch estimation using Self Supervised Learning (SSL).
no code implementations • 12 Jun 2023 • Laure Prétet, Gaël Richard, Clément Souchier, Geoffroy Peeters
We propose a novel approach to significantly improve the system's performance using structure-aware recommendation.
no code implementations • 15 Nov 2022 • Geoffroy Peeters, Florian Angulo
In this paper, we propose a new paradigm to learn audio features for Music Structure Analysis (MSA).
1 code implementation • 14 Nov 2022 • Karim M. Ibrahim, Elena V. Epure, Geoffroy Peeters, Gaël Richard
Namely, we propose a system which can generate a situational playlist for a user at a certain time 1) by leveraging user-aware music autotaggers, and 2) by automatically inferring the user's situation from stream data (e. g. device, network) and user's general profile information (e. g. age).
no code implementations • 18 Feb 2022 • Christof Weiß, Geoffroy Peeters
We therefore investigate the influence of dataset splits in the presence of several movements of a work cycle (cross-version evaluation) and propose a best-practice splitting strategy for MusicNet, which weakens the influence of individual test tracks and suppresses overfitting to specific works and recording conditions.
1 code implementation • 5 Aug 2020 • Gabriel Meseguer-Brocal, Geoffroy Peeters
These approaches use prior information about the target source to improve separation.
no code implementations • 18 May 2020 • Laure Prétet, Gaël Richard, Geoffroy Peeters
These algorithms aim at retrieving a ranked list of music tracks based on their similarity with a target music track.
1 code implementation • 22 Oct 2019 • 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.
no code implementations • 3 Jul 2019 • Guillaume Doras, Geoffroy Peeters
In this work, we propose a neural network architecture that is trained to represent each track as a single embedding vector.
2 code implementations • 2 Jul 2019 • Gabriel Meseguer-Brocal, Geoffroy Peeters
The input vector is embedded to obtain the parameters that control Feature-wise Linear Modulation (FiLM) layers.
2 code implementations • 25 Jun 2019 • Gabriel Meseguer-Brocal, Alice Cohen-Hadria, Geoffroy Peeters
We start with a set of manual annotations of draft time-aligned lyrics and notes made by non-expert users of Karaoke games.
3 code implementations • 3 May 2018 • Dominique Fourer, Geoffroy Peeters
We propose a novel unsupervised singing voice detection method which use single-channel Blind Audio Source Separation (BASS) algorithm as a preliminary step.
Sound Audio and Speech Processing