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Automatic Tagging Using Deep Convolutional Neural Networks
TLDR
We present a content-based automatic music tagging algorithm using Fully Convolutional neural networks (FCNs). Expand
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Convolutional recurrent neural networks for music classification
TLDR
We introduce a convolutional recurrent neural network (CRNN) for music tagging while controlling the number of parameters with respect to their performance and training time. Expand
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Transfer Learning for Music Classification and Regression Tasks
TLDR
We propose to use a pre-trained convnet feature, a concatenated feature vector using the activations of feature maps of multiple layers in a trained convolutional network for music classification and regression tasks. Expand
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Text-based LSTM networks for Automatic Music Composition
TLDR
In this paper, we introduce new methods and discuss results of text-based LSTM (Long Short-Term Memory) networks for automatic music composition. Expand
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A Tutorial on Deep Learning for Music Information Retrieval
TLDR
We present a tutorial on deep learning for Music Information Retrieval (MIR) research. Expand
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librosa/librosa: 0.6.0
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Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras
TLDR
We introduce Kapre, Keras layers for audio and music signal preprocessing. Expand
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Deep Learning for Audio-Based Music Classification and Tagging: Teaching Computers to Distinguish Rock from Bach
Over the last decade, music-streaming services have grown dramatically. Pandora, one company in the field, has pioneered and popularized streaming music by successfully deploying the Music GenomeExpand
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Explaining Deep Convolutional Neural Networks on Music Classification
TLDR
In this paper, we introduce auralisation of a CNN to understand its underlying mechanism, which is based on a deconvolution procedure introduced in [2]. Expand
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The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging
TLDR
We analyze and (re-)validate a large music tagging dataset to investigate the reliability of training and evaluation of DNNs. Expand
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