Music and Audio Computing Lab

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Performance Analysis and Resynthesis of Piano Music

Classical music often contains complicate musical structure and text compared to other genres of music. In this topic, we search for technical methods that can help listeners to understand and enjoy the classical music. One of the representative examples is web-based listening interface that provides a score of the piece with its various recordings, which are synchronized with the score. We also work on analyzing performer’s interpretation of the music, so that we can explain the differences among performances in a quantitative way.

PerformScore: Web-based Piano Score and Performance Analysis Visualization System [demo]


  • 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 (NIPS), 2018 (to appear)
  • 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]
  • Note Intensity Estimation of Piano Recordings by Score-informed NMF
    Dasaem Jeong and Juhan Nam
    Proceedings of the Audio Engineering Society Conference on Semantic Audio (AES), 2017 [pdf]


Dasaem Jeong, Taegyun Kwon and Juhan Nam


Samsung Research Funding, 2017-2020

중소기업기술정보진흥원 이공계창업꿈나무과제, 2016