Publications

Peer-reviewed Publications

• A Real-time Lyrics Alignment System Using Chroma and Phonetic Features For Classical Vocal Performance

  Jiyun Park, Sangeon Yong, Taegyun Kwon, and Juhan Nam

  International Conference on Acoustics, Speech Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024

  [Pdf]

• A Study of Audio Mixing Methods for Piano Transcription in Violin-Piano Ensembles

  Hyemi Kim, Jiyun Park, Taegyun Kwon, Dasaem Jeong, and Juhan Nam

  Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023

  [Pdf]

• YM2413-MDB: A Multi-Instrumental FM Video Game Music Dataset with Emotion Annotations

  Choi Eunjin, Yoonjin Chung, Seolhee Lee, Jongik Jeon, Taegyun Kwon and Juhan Nam

  Proceedings of the 23th International Society for Music Information Retrieval Conference (ISMIR), 2022

  [Pdf][Project Page]

• Polyphonic Piano Transcription Using Autoregressive Multi-State Note Model

  Taegyun Kwon, Dasaem Jeong, and Juhan Nam

  Proceedings of the 21th International Society for Music Information Retrieval Conference (ISMIR), 2020

  [Pdf][Project Page][AI:UM Demo(Korean)]

• Note Intensity Estimation of Piano Recordings Using Coarsely-aligned MIDI Score

  Dasaem Jeong, Taegyun Kwon, and Juhan Nam

  Journal of the Audio Engineering Society, 68 (1/2), 34-47, 2019.

  [Pdf]

• Hierarchical RNN-based System for Modeling Expressive Piano Performance

  Dasaem Jeong, Taegyun Kwon, Yoojin Kim, Kyogu Lee, and Juhan Nam

  Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), 2019

  [Pdf][Code]

• A Cross-Scape Plot Representation for Visualizing Symbolic Melodic Similarity

  Saebyul Park, Taegyun Kwon, Jongpil Lee, Jeounghoon Kim, and Juhan Nam

  Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), 2019

  [Pdf][Code]

• Graph Neural Network for Music Score Data and Modeling Expressive Piano Performance

  Dasaem Jeong, Taegyun Kwon, Yoojin Kim, and Juhan Nam

  Proceedings of the 36th International Conference on Machine Learning (ICML), 2019

  [Pdf]

• A Timbre-based Approach to Estimate Key Velocity from Polyphonic Piano Recordings

  Dasaem Jeong, Taegyun Kwon, and Juhan Nam

  Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), 2018

  [Pdf]

• Audio-to-Score Alignment Of Piano Music Using RNN-based Automatic Music Transcription

  Taegyun Kwon, Dasaem Jeong and Juhan Nam

  Proceedings of the 14th Sound and Music Computing Conference (SMC), 2017

  [Pdf][Demo]

Peer-reviewed Abstract & Workshop Articles

• Multivariate Kinematic Analysis of Piano Performance: A Case Study of A Professional Pianist

  Dawon Park, Taegyun Kwon, Joonhyung Bae, Jongwha Park, Juhan Nam and Jaebum Park

  International Society of Biomechanics (ISB), 2023

  [Pdf]

• Automated Gap-Filing Algorithm for Kinetic Data of Finger Movement: Pianist Hand Motion Cleaning using Spatio-Temporal Imputation

  Taegyun Kwon, Dawon Park, Joonhyung Bae, Jongwha Park, Juhan Nam and Jaebum Park

  International Society of Biomechanics (ISB), 2023

  [Pdf]

• Emotion Classification and Analysis of Expressive Performances in Classical Piano Music

  Yoojin Kim, Jeongmi Park, Dasaem Jeong, Taegyun Kwon, Jonghwa Park, Juhan Nam

  Proceedings of the 16th International Conference on Music Perception and Cognition (ICMPC16), 2021

• TräumerAI: Dreaming Music with StyleGAN

  Dasaem Jeong, Seungheon Doh, and Taegyun Kwon

  Workshop on Machine Learning for Creativity and Design, Neural Information Processing Systems (NeurIPS), 2020

  [Pdf][Project Page]

• Score and Performance Features for Rendering Expressive Music Performances

  Dasaem Jeong, Taegyun Kwon, Yoojin Kim, and Juhan Nam

  Proceedings of the Music Encoding Conference (MEC), 2019

  [Pdf]

• VirtuosoNet: A Hierarchical Attention RNN for Generating Expressive Piano Performance from Music Score

  Dasaem Jeong, Taegyun Kwon, and Juhan Nam

  Workshop on Machine Learning for Creativity and Design, Neural Information Processing Systems (NeurIPS), 2018

  [Pdf]

• PerformScore: Toward Performance Visualization With the Score on the Web Browser

  Dasaem Jeong, Taegyun Kwon, Chaelin Park, and Juhan Nam

  Late Breaking Demo in the 18th International Society for Musical Information Retrieval Conference (ISMIR), 2017

• Automatic DJ Mix Generation Using Highlight Detection

  Adrian Kim, Soram Park, Jangyeon Park, Jung-Woo Ha, Taegyun Kwon and Juhan Nam

  Late Breaking Demo in the 18th International Society for Musical Information Retrieval Conference (ISMIR), 2017