About me
Research Interests
- Music Information Retrieval
- Deep Learning
Career
- 2020 - now. CEO (Co-founder), Neutune, Seoul, South Korea
Education
- 2017 - 2021. PhD (Thesis), Graduate School of Culture Technology, KAIST, Daejeon, South Korea (Advisor: Juhan Nam)
- 2015 - 2017. MS, Graduate School of Culture Technology, KAIST, Daejeon, South Korea
- 2007 - 2015. BS, EE, Hanyang University, Seoul, South Korea
Experience
- 2020. Visiting PhD, Music and Audio Research Laboratory, New York University, New York City, United States
- 2019. Research Intern, Audio Research Group, Adobe, San Francisco, United States
- 2017. Research Intern, Clova Artificial Intelligence Research, Naver, Seongnam, South Korea
Tutorial
Metric Learning for Music Information Retrieval
Brian McFee, Jongpil Lee, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2020
Waveform-based Music Processing with Deep Learning
Jordi Pons, Jongpil Lee, and Sander DielemanInternational Society of Music Information Retrieval Conference (ISMIR), 2019
Journals
Semantic Tagging of Singing Voices in Popular Music Recordings
Keunhyoung Luke Kim, Jongpil Lee, Sangeun Kum, Chae Lin Park, and Juhan NamIEEE/ACM Transactions on Audio, Speech and Language Processing, 2020
Comparison and Analysis of SampleCNN Architectures for Audio Classification
Taejun Kim, Jongpil Lee, and Juhan NamIEEE Journal of Selected Topics in Signal Processing, 2019
Deep Learning for Audio-based Music Classification and Tagging: Teaching Computers to Distinguish Rock from Bach
Juhan Nam, Keunwoo Choi, Jongpil Lee, Szu-Yu Chou, and Yi-Hsuan YangIEEE Signal Processing Magazine, 2019
SampleCNN: End-to-End Deep Convolutional Neural Networks Using Very Small Filters for Music Classification
Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan NamApplied Sciences, 2018
Multi-Level and Multi-Scale Feature Aggregation Using Pre-trained Convolutional Neural Networks for Music Auto-tagging
Jongpil Lee, and Juhan NamIEEE Signal Processing Letters, 2017
Exhibition
NEUROSCAPE: Artificial Soundscape Based on Multimodal Connections of Deep Neural Networks
Seungsoon Park, Jongpil Lee, and Juhan NamInternational Computer Music Conference (ICMC), 2018
Conferences, Workshops, Challenges, Demos
Learning a Cross-domain Embedding Space of Vocal and Mixed Audio with a Structure-preserving Triplet Loss
Keunhyoung Luke Kim, Jongpil Lee, Sangeun Kum, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2021
Mixed Scape: Development of Framework and Artwork for Auditory Correspondence in Mixed Reality
Seungsoon Park, Jongpil Lee, Taewan Kim, Tae Hong Park, Joonhyung Bae, and Juhan NamInternational Computer Music Conference (ICMC), 2021
Metric Learning VS Classification for Disentangled Music Representation Learning
Jongpil Lee, Nicholas J. Bryan, Justin Salamon, Zeyu Jin, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2020
Musical Word Embedding: Bridging the Gap between Listening Contexts and Music
Seungheon Doh, Jongpil Lee, Tae Hong Park, and Juhan NamMachine Learning for Media Discovery Workshop, International Conference on Machine Learning (ICML), 2020
Disentangled Multidimensional Metric Learning for Music Similarity
Jongpil Lee, Nicholas J. Bryan, Justin Salamon, Zeyu Jin, and Juhan NamIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
*** IEEE SPS Student Travel Grant ***
Zero-shot Learning for Audio-based Music Classification and Tagging
Jeong Choi*, Jongpil Lee*, Jiyoung Park, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2019
* Equally contributed
A Cross-Scape Plot Representation for Visualizing Symbolic Melodic Similarity
Saebyul Park, Taegyun Kwon, Jongpil Lee, Jeounghoon Kim, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2019
Representation Learning of Music Using Artist, Album, and Track Information
Jongpil Lee, Jiyoung Park, and Juhan NamMachine Learning for Music Discovery Workshop, International Conference on Machine Learning (ICML), 2019
Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging
Jeong Choi, Jongpil Lee, Jiyoung Park, and Juhan NamMachine Learning for Music Discovery Workshop, International Conference on Machine Learning (ICML), 2019
Deep Content-User Embedding Model for Music Recommendation
Jongpil Lee, Kyungyun Lee, Jiyoung Park, Jangyeon Park, and Juhan Namhttps://arxiv.org/abs/1807.06786, 2018
Representation Learning of Music Using Artist Labels
Jiyoung Park*, Jongpil Lee*, Jangyeon Park, Jung-Woo Ha, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2018
* Equally contributed
A Hybrid of Deep Audio Feature and i-vector for Artist Recognition
Jiyoung Park, Donghyun Kim, Jongpil Lee, Sangeun Kum, and Juhan NamJoint Workshop on Machine Learning for Music, International Conference on Machine Learning (ICML), 2018
Sample-level CNN Architectures for Music Auto-tagging Using Raw Waveforms
Taejun Kim, Jongpil Lee, and Juhan NamIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
Raw Waveform-based Audio Classification Using Sample-level CNN Architectures
Jongpil Lee, Taejun Kim, Jiyoung Park, and Juhan NamMachine Learning for Audio Signal Processing Workshop, Neural Information Processing Systems (NIPS), 2017
Building K-POP Singing Voice Tag Dataset: A Progress Report
KeunHyoung Luke Kim, Sangeun Kum, Chae Lin Park, Jongpil Lee, Jiyoung Park, and Juhan NamLate-Breaking/Demo Session of International Society of Music Information Retrieval Conference (ISMIR), 2017
MUSIC GALAXY HITCHHIKER: 3D Web Music Navigation Through Audio Space Trained with Tag and Artist Labels
Dongwoo Suh, Kyungyun Lee, Jongpil Lee, Jiyoung Park, and Juhan NamLate-Breaking/Demo Session of International Society of Music Information Retrieval Conference (ISMIR), 2017
Cross-cultural Transfer Learning Using Sample-level Deep Convolutional Neural Networks
Jongpil Lee, Jiyoung Park, Chanju Kim, Adrian Kim, Jangyeon Park, Jung-Woo Ha, and Juhan NamMusic Information Retrieval Evaluation eXchange (MIREX), 2017
1st place in the four K-POP tasks across all algorithms submitted so far
Representation Learning Using Artist labels for Audio Classification Tasks
Jiyoung Park, Jongpil Lee, Jangyeon Park, Jung-Woo Ha, and Juhan NamMusic Information Retrieval Evaluation eXchange (MIREX), 2017
1st place in the Music Mood Classification task across all algorithms submitted so far
Combining Multi-Scale Features Using Sample-level Deep Convolutional Neural Networks for Weakly Supervised Sound Event Detection
Jongpil Lee, Jiyoung Park, Sangeun Kum, Youngho Jeong, and Juhan NamProceedings of the 2nd Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), 2017
Multi-Level and Multi-Scale Feature Aggregation Using Sample-level Deep Convolutional Neural Networks for Music Classification
Jongpil Lee, and Juhan NamMachine Learning for Music Discovery Workshop, International Conference on Machine Learning (ICML), 2017
Sample-level Deep Convolutional Neural Networks for Music Auto-tagging Using Raw Waveforms
Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan NamSound and Music Computing Confenrence (SMC), 2017
The Effect of DJs’ Social Network on Music Popularity
Hyeongseok Wi, Kyung hoon Hyun, Jongpil Lee, and Wonjae LeeInternational Computer Music Conference (ICMC), 2016
Contact
- jongpillee.brian (at) gmail.com
- richter (at) kaist.ac.kr
