Convolutional Recurrent Neural Networks for Music Classification

2016/09/14 by Keunwoo Choi, Choi, Keunwoo, George Fazekas +5 · 5 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimedia (cs.MM) #Music Technology and Sound Studies #Music and Audio Processing #Neural and Evolutionary Computing (cs.NE) #Sound (cs.SD) #Speech and Audio Processing

paper · pdf · doi:10.48550/arxiv.1609.04243

openalex publication_date 2016/09/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We introduce a convolutional recurrent neural network (CRNN) for music tagging. CRNNs take advantage of convolutional neural networks (CNNs) for local feature extraction and recurrent neural networks for temporal summarisation of the extracted features. We compare CRNN with three CNN structures that have been used for music tagging while controlling the number of parameters with respect to their performance and training time per sample. Overall, we found that CRNNs show a strong performance with respect to the number of parameter and training time, indicating the effectiveness of its hybrid structure in music feature extraction and feature summarisation.

Citations

• On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
• Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
• The Power of Depth for Feedforward Neural Networks
• Automatic tagging using deep convolutional neural networks

Cited by

• MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation
• Spectral and Rhythm Feature Performance Evaluation for Category and Class Level Audio Classification with Deep Convolutional Neural Networks
• Perceptual and automated estimates of infringement in 40 music copyright cases
• Sample-level Deep Convolutional Neural Networks for Music Auto-tagging Using Raw Waveforms
• Content-Based Video-Music Retrieval Using Soft Intra-Modal Structure Constraint

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• Automatic tagging using deep convolutional neural networks
• Sample-level CNN Architectures for Music Auto-tagging Using Raw Waveforms
• musicnn: Pre-trained convolutional neural networks for music audio tagging
• Music Artist Classification with Convolutional Recurrent Neural Networks
• Sample-level Deep Convolutional Neural Networks for Music Auto-tagging Using Raw Waveforms