224 citations · 767 across the 33 of their papers we have counts for
6 papers · 1 filter
DLR : Toward a deep learned rhythmic representation for music content analysis
Yeonwoo Jeong, Keunwoo Choi, Hosan Jeong
In the use of deep neural networks, it is crucial to provide appropriate input representations for the network to learn from. In this paper, we propose an approach to learn a repre…
A Tutorial on Deep Learning for Music Information Retrieval
Keunwoo Choi, György Fazekas, Kyunghyun Cho +1
Following their success in Computer Vision and other areas, deep learning techniques have recently become widely adopted in Music Information Retrieval (MIR) research. However, the…
A Comparison of Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging
Keunwoo Choi, György Fazekas, Kyunghyun Cho +1
In this paper, we empirically investigate the effect of audio preprocessing on music tagging with deep neural networks. We perform comprehensive experiments involving audio preproc…
Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras
Keunwoo Choi, Deokjin Joo, Juho Kim
We introduce Kapre, Keras layers for audio and music signal preprocessing. Music research using deep neural networks requires a heavy and tedious preprocessing stage, for which aud…
The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging
Keunwoo Choi, George Fazekas, Kyunghyun Cho +1
Deep neural networks (DNN) have been successfully applied to music classification including music tagging. However, there are several open questions regarding the training, evaluat…
Transfer learning for music classification and regression tasks
Keunwoo Choi, György Fazekas, Mark Sandler +1
In this paper, we present a transfer learning approach for music classification and regression tasks. We propose to use a pre-trained convnet feature, a concatenated feature vector…