Multi-Step Chord Sequence Prediction Based on Aggregated Multi-Scale Encoder-Decoder Network

1 code implementation • 12 Nov 2019 • Tristan Carsault, Andrew McLeod, Philippe Esling, Jérôme Nika, Eita Nakamura, Kazuyoshi Yoshii

In this paper, we postulate that this comes from the multi-scale structure of musical information and propose new architectures based on an iterative temporal aggregation of input labels.

Using musical relationships between chord labels in automatic chord extraction tasks

1 code implementation • 12 Nov 2019 • Tristan Carsault, Jérôme Nika, Philippe Esling

Recent researches on Automatic Chord Extraction (ACE) have focused on the improvement of models based on machine learning.

Semi-supervised Neural Chord Estimation Based on a Variational Autoencoder with Latent Chord Labels and Features

1 code implementation • 14 May 2020 • Yiming Wu, Tristan Carsault, Eita Nakamura, Kazuyoshi Yoshii

In contrast, we propose a unified generative and discriminative approach in the framework of amortized variational inference.

General Classification Variational Inference

Ultra-light deep MIR by trimming lottery tickets

1 code implementation • 31 Jul 2020 • Philippe Esling, Theis Bazin, Adrien Bitton, Tristan Carsault, Ninon Devis

We show that our proposal can remove up to 90% of the model parameters without loss of accuracy, leading to ultra-light deep MIR models.

Audio Classification Drum Transcription +3