Jongmin Jung

About

I solve problems in a witty manner.

My research focuses on developing Generative Music Intelligence, structured around three interconnected research directions: inter-modal understanding, controllable generation, and disentangled music representation.

Publications

U-MusT: Unified Cross-modal Translation of Score Images, Symbolic Music, and Performance Audio Jongmin Jung, Dongmin Kim, Sihun Lee, Seola Cho, Hyungjoon Soh, Irmak Bukey, Chris Donahue, Dasaem Jeong IEEE Transactions on Audio, Speech, and Language Processing (TASLP)

Demo

2025

From Generation to Attribution: Music AI Agent Architectures for the Post-Streaming Era Wonil Kim, Hyeongseok Wi, Seungsoon Park, Taejun Kim, Sangeun Keum, Keunhyoung Kim, Taewan Kim, Jongmin Jung, Taehyoung Kim, Gaetan Guerrero, Mael Le Goff, Julie Po, Dongjoo Moon, Juhan Nam, Jongpil Lee NeurIPS Workshop on AI for Music

Demo

2025

LAV: Audio-Driven Dynamic Visual Generation with Neural Compression and StyleGAN2 Jongmin Jung, Dasaem Jeong The 30th International Symposium on Electronic/Emerging Art (ISEA)

Demo

2025

MusicGen-Chord: Advancing Music Generation through Chord Progressions and Interactive Web-UI Jongmin Jung, Andreas Jansson, Dasaem Jeong Late-breaking/Demo at the 25th International Society of Music Information Retrieval Conference (ISMIR)

Demo

2024

Nested Music Transformer: Sequentially Decoding Compound Tokens in Symbolic Music and Audio Generation Jiwoo Ryu, Hao-Wen Dong, Jongmin Jung, Dasaem Jeong The 25th International Society of Music Information Retrieval Conference (ISMIR)

2024

K-pop Lyric Translation: Dataset, Analysis, and Neural-Modelling Haven Kim, Jongmin Jung, Dasaem Jeong, Juhan Nam The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-Coling)

2024

Work Title