105 citations · 210 across the 8 of their papers we have counts for
8 papers
Zero-shot Learning for Audio-based Music Classification and Tagging
Jeong Choi, Jongpil Lee, Jiyoung Park +1
Audio-based music classification and tagging is typically based on categorical supervised learning with a fixed set of labels. This intrinsically cannot handle unseen labels such a…
Representation Learning of Music Using Artist, Album, and Track Information
Jongpil Lee, Jiyoung Park, Juhan Nam
Supervised music representation learning has been performed mainly using semantic labels such as music genres. However, annotating music with semantic labels requires time and cost…
Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging
Jeong Choi, Jongpil Lee, Jiyoung Park +1
Music classification and tagging is conducted through categorical supervised learning with a fixed set of labels. In principle, this cannot make predictions on unseen labels. Zero-…
A Hybrid of Deep Audio Feature and i-vector for Artist Recognition
Jiyoung Park, Donghyun Kim, Jongpil Lee +2
Artist recognition is a task of modeling the artist's musical style. This problem is challenging because there is no clear standard. We propose a hybrid method of the generative mo…
Deep Content-User Embedding Model for Music Recommendation
Jongpil Lee, Kyungyun Lee, Jiyoung Park +2
Recently deep learning based recommendation systems have been actively explored to solve the cold-start problem using a hybrid approach. However, the majority of previous studies p…
Raw Waveform-based Audio Classification Using Sample-level CNN Architectures
Jongpil Lee, Taejun Kim, Jiyoung Park +1
Music, speech, and acoustic scene sound are often handled separately in the audio domain because of their different signal characteristics. However, as the image domain grows rapid…
Representation Learning of Music Using Artist Labels
Jiyoung Park, Jongpil Lee, Jangyeon Park +2
In music domain, feature learning has been conducted mainly in two ways: unsupervised learning based on sparse representations or supervised learning by semantic labels such as mus…
Sample-level Deep Convolutional Neural Networks for Music Auto-tagging Using Raw Waveforms
Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim +1
Recently, the end-to-end approach that learns hierarchical representations from raw data using deep convolutional neural networks has been successfully explored in the image, text…