32 citations · 106 across the 16 of their papers we have counts for
3 papers · 1 filter
Tatum-Level Drum Transcription Based on a Convolutional Recurrent Neural Network with Language Model-Based Regularized Training
Ryoto Ishizuka, Ryo Nishikimi, Eita Nakamura +1
This paper describes a neural drum transcription method that detects from music signals the onset times of drums at the level, where tatum times are assumed to be…
Non-Local Musical Statistics as Guides for Audio-to-Score Piano Transcription
Kentaro Shibata, Eita Nakamura, Kazuyoshi Yoshii
We present an automatic piano transcription system that converts polyphonic audio recordings into musical scores. This has been a long-standing problem of music information process…
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…