| Graph neural network for music score data and modeling expressive piano performance D Jeong, T Kwon, Y Kim, J Nam International Conference on Machine Learning (ICML), 3060-3070, 2019 | 62 | 2019 |
| VirtuosoNet: A Hierarchical RNN-based System for Modeling Expressive Piano Performance D Jeong, T Kwon, Y Kim, K Lee, J Nam 20th International Society for Music Information Retrieval Conference (ISMIR), 2019 | 60 | 2019 |
| Audio-to-score alignment of piano music using RNN-based automatic music transcription T Kwon, D Jeong, J Nam 14th Sound and Music Computing Conference (SMC), 2017 | 34 | 2017 |
| Polyphonic piano transcription using autoregressive multi-state note model T Kwon, D Jeong, J Nam 21st International Society for Music Information Retrieval Conference (ISMIR), 2020 | 20 | 2020 |
| Score and Performance Features for Rendering Expressive Music Performances D Jeong, T Kwon, Y Kim, J Nam Music Encoding Conference 2019, 2019 | 16 | 2019 |
| TräumerAI: Dreaming Music with StyleGAN D Jeong, S Doh, T Kwon NeurIPS 2020 Workshop: Machine Learning for Creativity and Design, 2020 | 13 | 2020 |
| Note intensity estimation of piano recordings by score-informed nmf D Jeong, J Nam Audio Engineering Society Conference: 2017 AES International Conference on …, 2017 | 11 | 2017 |
| Visualizing Music in its Entirety using Acoustic Features: Music Flowgram D Jeong, J Nam 2nd International Conference on Technologies for Music Notation and …, 2016 | 10 | 2016 |
| Automatic piano fingering from partially annotated scores using autoregressive neural networks P Ramoneda, D Jeong, E Nakamura, X Serra, M Miron Proceedings of the 30th ACM International Conference on Multimedia, 6502-6510, 2022 | 7 | 2022 |
| Note-intensity estimation of piano recordings using coarsely aligned midi score D Jeong, T Kwon, J Nam Journal of the Audio Engineering Society 68 (1/2), 34-47, 2020 | 7 | 2020 |
| VirtuosoNet: A Hierarchical Attention RNN for Generating Expressive Piano Performance from Music Score D Jeong, T Kwon, J Nam NeurIPS 2018 Workshop on Machine Learning for Creativity and Design, 2018 | 7 | 2018 |
| PerformScore: TOWARD PERFORMANCE VISUALIZATION WITH THE SCORE ON THE WEB BROWSER D Jeong, T Kwon, C Park, J Nam Late Breaking / Demo in The 18th International Society for Music Information …, 2017 | 6 | 2017 |
| A Timbre-based Approach To Estimate Key Velocity From Polyphonic Piano Recordings D Jeong, T Kwon, J Nam 19th International Society for Music Information Retrieval Conference (ISMIR), 2018 | 5 | 2018 |
| Combining piano performance dimensions for score difficulty classification P Ramoneda, D Jeong, V Eremenko, NC Tamer, M Miron, X Serra Expert Systems with Applications 238, 121776, 2024 | 4 | 2024 |
| Annotator Subjectivity in the MusicCaps Dataset M Lee, SH Doh, D Jeong 2nd Workshop on Human-Centric Music Information Research (HCMIR23), 2023 | 3 | 2023 |
| Real-time Automatic Piano Music Transcription System D Jeong Late Breaking / Demo (LBD) of 21st International Society for Music …, 2020 | 3 | 2020 |
| Can Audio Reveal Music Performance Difficulty? Insights from the Piano Syllabus Dataset P Ramoneda, M Lee, D Jeong, JJ Valero-Mas, X Serra arXiv preprint arXiv:2403.03947, 2024 | 2 | 2024 |
| Predicting performance difficulty from piano sheet music images P Ramoneda, JJ Valero-Mas, D Jeong, X Serra arXiv preprint arXiv:2309.16287, 2023 | 2 | 2023 |
| K-pop Lyric Translation: Dataset, Analysis, and Neural-Modelling H Kim, J Jung, D Jeong, J Nam arXiv preprint arXiv:2309.11093, 2023 | 2 | 2023 |
| Six dragons fly again: Reviving 15th-century korean court music with transformers and novel encoding D Han, M Gotham, D Kim, H Park, S Lee, D Jeong arXiv preprint arXiv:2408.01096, 2024 | 1 | 2024 |
Juhan NamKAIST在 kaist.ac.kr 的电子邮件经过验证
