Music Transcription

33 papers with code • 1 benchmarks • 7 datasets

Music transcription is the task of converting an acoustic musical signal into some form of music notation.

( Image credit: ISMIR 2015 Tutorial - Automatic Music Transcription )


Use these libraries to find Music Transcription models and implementations

Most implemented papers

Deep Complex Networks

ChihebTrabelsi/deep_complex_networks ICLR 2018

Despite their attractive properties and potential for opening up entirely new neural architectures, complex-valued deep neural networks have been marginalized due to the absence of the building blocks required to design such models.

MT3: Multi-Task Multitrack Music Transcription

magenta/mt3 ICLR 2022

Automatic Music Transcription (AMT), inferring musical notes from raw audio, is a challenging task at the core of music understanding.

Music transcription modelling and composition using deep learning

IraKorshunova/folk-rnn 29 Apr 2016

We apply deep learning methods, specifically long short-term memory (LSTM) networks, to music transcription modelling and composition.

Learning Features of Music from Scratch

benadar293/ 29 Nov 2016

This paper introduces a new large-scale music dataset, MusicNet, to serve as a source of supervision and evaluation of machine learning methods for music research.

Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences

LUMII-Syslab/RSE 6 Apr 2020

Attention is a commonly used mechanism in sequence processing, but it is of O(n^2) complexity which prevents its application to long sequences.

The Effect of Spectrogram Reconstruction on Automatic Music Transcription: An Alternative Approach to Improve Transcription Accuracy

KinWaiCheuk/ICPR2020 20 Oct 2020

We attempt to use only the pitch labels (together with spectrogram reconstruction loss) and explore how far this model can go without introducing supervised sub-tasks.

Sequence-to-Sequence Piano Transcription with Transformers

Aolin-MIR/Sequence-to-Sequence-Piano-Transcription-with-Transformers 19 Jul 2021

Automatic Music Transcription has seen significant progress in recent years by training custom deep neural networks on large datasets.

An End-to-End Neural Network for Polyphonic Piano Music Transcription

9552nZ/SmartSheetMusic 7 Aug 2015

We compare performance of the neural network based acoustic models with two popular unsupervised acoustic models.

Deep convolutional neural networks for predominant instrument recognition in polyphonic music

iooops/CS221-Audio-Tagging 31 May 2016

We train our network from fixed-length music excerpts with a single-labeled predominant instrument and estimate an arbitrary number of predominant instruments from an audio signal with a variable length.

Optimal spectral transportation with application to music transcription

rflamary/OST NeurIPS 2016

Many spectral unmixing methods rely on the non-negative decomposition of spectral data onto a dictionary of spectral templates.