no code implementations • 30 Nov 2023 • Axel Marmoret, Jérémy E. Cohen, Frédéric Bimbot
Music Structure Analysis (MSA) is a Music Information Retrieval task consisting of representing a song in a simplified, organized manner by breaking it down into sections typically corresponding to ``chorus'', ``verse'', ``solo'', etc.
no code implementations • 27 Oct 2022 • Axel Marmoret, Jérémy E. Cohen, Frédéric Bimbot
In particular, the CBM algorithm is a dynamic programming algorithm, applying on autosimilarity matrices, a standard tool in MSA.
1 code implementation • 10 Feb 2022 • Haoran Wu, Axel Marmoret, Jérémy E. Cohen
Automatic Music Transcription, which consists in transforming an audio recording of a musical performance into symbolic format, remains a difficult Music Information Retrieval task.
no code implementations • 10 Feb 2022 • Axel Marmoret, Jérémy E. Cohen, Frédéric Bimbot
More specifically, under the hypothesis that MSA is correlated with similarities occurring at the bar scale, this article introduces the use of linear and non-linear compression schemes on barwise audio signals.
1 code implementation • 27 Oct 2021 • Axel Marmoret, Jérémy E. Cohen, Frédéric Bimbot
The ability of deep neural networks to learn complex data relations and representations is established nowadays, but it generally relies on large sets of training data.
2 code implementations • 27 Oct 2021 • Axel Marmoret, Florian Voorwinden, Valentin Leplat, Jérémy E. Cohen, Frédéric Bimbot
Nonnegative Tucker decomposition (NTD), a tensor decomposition model, has received increased interest in the recent years because of its ability to blindly extract meaningful patterns, in particular in Music Information Retrieval.
1 code implementation • 17 Apr 2021 • Axel Marmoret, Jérémy E. Cohen, Nancy Bertin, Frédéric Bimbot
Recent work has proposed the use of tensor decomposition to model repetitions and to separate tracks in loop-based electronic music.
no code implementations • 27 Aug 2018 • Jérémy E. Cohen, Nicolas Gillis
In this work, we provide new results in the deterministic scenario when the data has a low-rank structure, that is, when $D$ is (under)complete.
no code implementations • 3 Apr 2017 • Jérémy E. Cohen, Nicolas Gillis
To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary.