58 citations · 248 across the 23 of their papers we have counts for
5 papers · 1 filter
Music Classification: Beyond Supervised Learning, Towards Real-world Applications
Minz Won, Janne Spijkervet, Keunwoo Choi
Music classification is a music information retrieval (MIR) task to classify music items to labels such as genre, mood, and instruments. It is also closely related to other concept…
Semi-Supervised Music Tagging Transformer
Minz Won, Keunwoo Choi, Xavier Serra
We present Music Tagging Transformer that is trained with a semi-supervised approach. The proposed model captures local acoustic characteristics in shallow convolutional layers, th…
SpecTNT: a Time-Frequency Transformer for Music Audio
Wei-Tsung Lu, Ju-Chiang Wang, Minz Won +2
Transformers have drawn attention in the MIR field for their remarkable performance shown in natural language processing and computer vision. However, prior works in the audio proc…
Decoupling Magnitude and Phase Estimation with Deep ResUNet for Music Source Separation
Qiuqiang Kong, Yin Cao, Haohe Liu +2
Deep neural network based methods have been successfully applied to music source separation. They typically learn a mapping from a mixture spectrogram to a set of source spectrogra…
Listen, Read, and Identify: Multimodal Singing Language Identification of Music
Keunwoo Choi, Yuxuan Wang
We propose a multimodal singing language classification model that uses both audio content and textual metadata. LRID-Net, the proposed model, takes an audio signal and a language…