Music and Culture Technology Lab

We develop innovative music technologies.


We are interested in the technology for "machine musicianship," the dream of making machines’ understanding of music like musicians’. Research topics for this interdisciplinary direction encompass automatic music transcription, machine music appreciation, automatic music generation, and computational creativity of music. Applications will be found in music production, education, entertainment, well-being, computational musicology, and others related to next-generation music industry.

What's New

Four papers accepted by ISMIR 2018 !

  • Wei-Tsung Lu and Li Su, “Transferring the Style of Homophonic Music Using Recurrent Neural Networks and Autoregressive Model,” International Society of Music Information Retrieval Conference (ISMIR), September 2018.
  • Yin-Jyun Luo and Li Su, “Learning Domain-adaptive Latent Representations of Music Signals Using Variational Autoencoders,” International Society of Music Information Retrieval Conference (ISMIR), September 2018.
  • Tsung-Ping Chen and Li Su, “Functional Harmony Recognition with Multi-task Recurrent Neural Networks,” International Society of Music Information Retrieval Conference (ISMIR), September 2018.
  • Wei-Tsung Lu and Li Su, “Vocal melody extraction with semantic segmentation and audio-symbolic domain transfer learning,” International Society of Music Information Retrieval Conference (ISMIR), September 2018.

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