Song-Rong, Lee (李松融)

• Email: hubert.lee@mirlab.org
• Laboratory: Multimedia Information Retrieval Lab

Education

Master Student

• Department of Computer Science & Information Engineering, National Taiwan University
  July, 2019 ~ Present

Bachelor

• EECS Undergraduate Honors Program, National Chiao Tung University
  Sep, 2015 ~ June, 2019

Non-Degree

• Department of Computer Science, University of Illinois Urbana-Champaign
  Fall Semester Aug, 2018 ~ Dec, 2018

Projects

• Singing Voice Conversion
• MIR Lab GPU Tracker
• MIREX 2019 Audio Chord Estimation
• Singing Voice Separation Demo Website
• Distance-based Machine Learning Algorithm Research and Improvement
• Android Bluetooth Pedometer Social Communication Application Development
• Web Application for National Chiao Tung University Sports Week
• iTrust--Web Application for UIUC Course CS 427

References

Singing Voice Conversion

• Deng, Chengqi, et al. "Pitchnet: Unsupervised Singing Voice Conversion with Pitch Adversarial Network." ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020.
• Nachmani, Eliya, and Lior Wolf. "Unsupervised singing voice conversion." arXiv preprint arXiv:1904.06590 (2019).
• Mor, Noam, et al. "A universal music translation network." arXiv preprint arXiv:1805.07848 (2018).
• Engel, Jesse, et al. "Neural audio synthesis of musical notes with wavenet autoencoders." International Conference on Machine Learning. 2017.
• Chen, Xin, et al. "Singing voice conversion with non-parallel data." 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2019.
• Lu, Junchen, et al. "VAW-GAN for Singing Voice Conversion with Non-parallel Training Data." 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2020.

Guitar Playing Assessment

• Harte, Christopher, Mark Sandler, and Martin Gasser. "Detecting harmonic change in musical audio." Proceedings of the 1st ACM workshop on Audio and music computing multimedia. ACM, 2006.
• Ono, Nobutaka, et al. "A Real-time Equalizer of Harmonic and Percussive Components in Music Signals." ISMIR. 2008.
• Jiang, Dan-Ning, et al. "Music type classification by spectral contrast feature." Proceedings. IEEE International Conference on Multimedia and Expo. Vol. 1. IEEE, 2002.
• Wright, Benjamin D., and Magdalena Mok. "Understanding Rasch measurement: Rasch models overview." Journal of applied measurement (2000).
• Silverman, Michael J. "Developing and testing the guitar songleading performance scale (GSPS)." International Journal of Music Education 29.3 (2011): 283-293.
• Russell, Brian E. "The development of a guitar performance rating scale using a facet-factorial approach." Bulletin of the Council for Research in Music Education (2010): 21-34.
• Kandadai, Srivatsan, Joseph Hardin, and Charles D. Creusere. "Audio quality assessment using the mean structural similarity measure." 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008.
• Rix, Antony W., et al. "Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs." 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No. 01CH37221). Vol. 2. IEEE, 2001.
• Rix, Antony W., et al. "Objective assessment of speech and audio quality—technology and applications." IEEE Transactions on Audio, Speech, and Language Processing 14.6 (2006): 1890-1901.
• Seyerlehner, Klaus, et al. "Using block-level features for genre classification, tag classification and music similarity estimation." Submission to Audio Music Similarity and Retrieval Task of MIREX 2010 (2010).
• Pohle, Tim, et al. "On Rhythm and General Music Similarity." ISMIR. 2009.
• Pampalk, Elias. "Computational models of music similarity and their application in music information retrieval." PhD thesis, Technischen Universitat Wien (2006).
• Ferm Almqvist, Cecilia, et al. "Assessment as learning in music education: The risk of “criteria compliance” replacing “learning” in the Scandinavian countries." Research Studies in Music Education 39.1 (2017): 3-18.
• Asmus, Edward P. "Music assessment concepts: a discussion of assessment concepts and models for student assessment introduces this special focus issue." Music educators journal 86.2 (1999): 19-24.

Singing Voice Separation

• Jansson, Andreas et al. “Singing Voice Separation with Deep U-Net Convolutional Networks.” ISMIR (2017).

Other Links

• Github
• Hubert's Coding Notes

Last updated on 2021/05/18