Music Transcription
36 papers with code • 2 benchmarks • 9 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 )
Libraries
Use these libraries to find Music Transcription models and implementationsDatasets
MAESTRO
MusicNet
Music21
Slakh2100
ASAP (Aligned Scores and Performances)
CocoChorales
JS Fake Chorales
EGDB
ErhuPT
Most implemented papers
Optimal spectral transportation with application to music transcription
Many spectral unmixing methods rely on the non-negative decomposition of spectral data onto a dictionary of spectral templates.
Efficient Learning of Harmonic Priors for Pitch Detection in Polyphonic Music
Automatic music transcription (AMT) aims to infer a latent symbolic representation of a piece of music (piano-roll), given a corresponding observed audio recording.
Onsets and Frames: Dual-Objective Piano Transcription
BShakhovsky/PolyphonicPianoTranscription
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We advance the state of the art in polyphonic piano music transcription by using a deep convolutional and recurrent neural network which is trained to jointly predict onsets and frames.
Invariances and Data Augmentation for Supervised Music Transcription
jthickstun/thickstun2018invariances
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This paper explores a variety of models for frame-based music transcription, with an emphasis on the methods needed to reach state-of-the-art on human recordings.
Towards multi-instrument drum transcription
In this work, convolutional and convolutional recurrent neural networks are trained to transcribe a wider range of drum instruments.
Complex Gated Recurrent Neural Networks
v0lta/Complex-gated-recurrent-neural-networks
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NeurIPS 2018
Complex numbers have long been favoured for digital signal processing, yet complex representations rarely appear in deep learning architectures.
Musical Instrument Playing Technique Detection Based on FCN: Using Chinese Bowed-Stringed Instrument as an Example
The effectiveness of the proposed framework is tested on a new dataset, its categorization of techniques is similar to our training dataset.
Complex Transformer: A Framework for Modeling Complex-Valued Sequence
While deep learning has received a surge of interest in a variety of fields in recent years, major deep learning models barely use complex numbers.
A holistic approach to polyphonic music transcription with neural networks
We present a framework based on neural networks to extract music scores directly from polyphonic audio in an end-to-end fashion.
Bayesian Sparsification Methods for Deep Complex-valued Networks
With continual miniaturization ever more applications of deep learning can be found in embedded systems, where it is common to encounter data with natural complex domain representation.
