Music Information Retrieval

98 papers with code • 0 benchmarks • 23 datasets

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Most implemented papers

Music Artist Classification with Convolutional Recurrent Neural Networks

ZainNasrullah/music-artist-classification-crnn 14 Jan 2019

To this end, an established classification architecture, a Convolutional Recurrent Neural Network (CRNN), is applied to the artist20 music artist identification dataset under a comprehensive set of conditions.

Revisiting Singing Voice Detection: a Quantitative Review and the Future Outlook

kyungyunlee/ismir2018-revisiting-svd 4 Jun 2018

Since the vocal component plays a crucial role in popular music, singing voice detection has been an active research topic in music information retrieval.

Optical Music Recognition with Convolutional Sequence-to-Sequence Models

eelcovdw/mono-musicxml-dataset 16 Jul 2017

This data set is the first publicly available set in OMR research with sufficient size to train and evaluate deep learning models.

Rethinking CNN Models for Audio Classification

kamalesh0406/Audio-Classification 22 Jul 2020

Besides, we show that even though we use the pretrained model weights for initialization, there is variance in performance in various output runs of the same model.

GiantMIDI-Piano: A large-scale MIDI dataset for classical piano music

bytedance/GiantMIDI-Piano 11 Oct 2020

In this article, we create a GiantMIDI-Piano (GP) dataset containing 38, 700, 838 transcribed notes and 10, 855 unique solo piano works composed by 2, 786 composers.

Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning

mimbres/neural-audio-fp 22 Oct 2020

Most of existing audio fingerprinting systems have limitations to be used for high-specific audio retrieval at scale.

A Tutorial on Deep Learning for Music Information Retrieval

keunwoochoi/mir_deepnet_tutorial 13 Sep 2017

Following their success in Computer Vision and other areas, deep learning techniques have recently become widely adopted in Music Information Retrieval (MIR) research.

Singing Voice Separation Using a Deep Convolutional Neural Network Trained by Ideal Binary Mask and Cross Entropy

EdwardLin2014/CNN-with-IBM-for-Singing-Voice-Separation 4 Dec 2018

We present a unique neural network approach inspired by a technique that has revolutionized the field of vision: pixel-wise image classification, which we combine with cross entropy loss and pretraining of the CNN as an autoencoder on singing voice spectrograms.

Improving Machine Hearing on Limited Data Sets

hararticles/gs-ms-mt 21 Mar 2019

In this contribution we investigate how input and target representations interplay with the amount of available training data in a music information retrieval setting.

Learning a Representation for Cover Song Identification Using Convolutional Neural Network

yzspku/CQTNet arXiv 2019

We first train the network through classification strategies; the network is then used to extract music representation for cover song identification.