Pattern recognition (psychology)

Feature (linguistics)

Machine learning

Recurrent neural network

Philosophy

Artificial intelligence

Computer science

Linguistics

Feature extraction

Speech recognition

Artificial neural network

Convolutional neural network

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.

Convolutional recurrent neural networks for music classification