12 citations · 14 across the 4 of their papers we have counts for
4 papers
Ultra-light deep MIR by trimming lottery tickets
Philippe Esling, Theis Bazin, Adrien Bitton +2
Current state-of-the-art results in Music Information Retrieval are largely dominated by deep learning approaches. These provide unprecedented accuracy across all tasks. However, t…
Semi-supervised Neural Chord Estimation Based on a Variational Autoencoder with Latent Chord Labels and Features
Yiming Wu, Tristan Carsault, Eita Nakamura +1
This paper describes a statistically-principled semi-supervised method of automatic chord estimation (ACE) that can make effective use of music signals regardless of the availabili…
Using musical relationships between chord labels in automatic chord extraction tasks
Tristan Carsault, Jérôme Nika, Philippe Esling
Recent researches on Automatic Chord Extraction (ACE) have focused on the improvement of models based on machine learning. However, most models still fail to take into account the…
Multi-Step Chord Sequence Prediction Based on Aggregated Multi-Scale Encoder-Decoder Network
Tristan Carsault, Andrew McLeod, Philippe Esling +3
This paper studies the prediction of chord progressions for jazz music by relying on machine learning models. The motivation of our study comes from the recent success of neural ne…