Introduction

Graduating from Jilin University as a computer science B.S., I achieved M.S. from Peking University, where I was fortunate to engage in the research of music technology, an interdisciplinary field between music and computer science. During my master study, I discovered my passion for research and determined to pursue a doctoral study.

In 2021, I obtained a Ph.D. degree (music technology) from Distributed Digital Music Archives & Libraries Lab at McGill University. My primary research topic is automatic harmonic analysis, and I am generally interested in applied machine learning, music information retrieval, music theory, and digital music libraries. I used to work at Tencent Music Entertainment as a Senior Researcher to develop AI music applications for QQ Music (2020-2022), and now I am a principal engineer at Huawei 2012 Laboratory, Central Media Technology Institute leading relevant music research/application projects.

Education

• Jilin University (JLU), Changchun, China (Sep. 2009–July 2013)

  • B.S. in School of Computer Science and Technology
  • Major: Computer Science and Technology
  • Thesis: The Research of Automatic Music Arrangement (Honors)
  • Advisor: Prof. Lan Huang
  • GPA: 3.73/4.00, recommended for admission of Peking University for graduate study

• Peking University, Beijing, China (Sep. 2013–July 2016)

  • M.S. in School of Electronics Engineering and Computer Science
  • Major: Intelligence Science and Technology
  • Thesis: Research on Automatic Chord Arrangement Based on Deep Recurrent Neural Networks
  • Supervisor: Prof. Xihong Wu
  • GPA: 3.62/4.00

• McGill University, Montreal, Canada (Sep. 2016–2021)

  • Ph.D. in Schulich School of Music
  • Major: Music Technology
  • Thesis: Addressing Ambiguity in Machine Learning: A Case Study in Automatic Chord Labelling
  • Supervisors: Prof. Ichiro Fujinaga and Prof. Cory McKay
  • GPA: 3.90/4.00

Selected Awards and Honors

• Jilin University
  • National Grant (Oct. 2010)
  • Self-reliance and Independent Student Honor (May 2011)
  • National Encouragement Scholarship (2010–2012)
  • School Outstanding Student (2010–2012)
  • Chinese Computer Federation (CCF) Scholarship (Oct. 2012)
  • Top 100 Outstanding Students of CCF in 2012 (Oct. 2012)
  • Xianzi Zeng Educational Fund (2011–2013)
  • Nominee of Top 10 Outstanding Student of Jilin University in 2012 (Oct. 2012)

• Peking University

  • Graduate Special Scholarship (Oct. 2014)
  • Graduate Fellowship (2013–2015)

• McGill University

  • CIRMMT Agile Seed Funding (Nov. 2019)
  • Interdisciplinary Research Project Seed Grant (June 2017, June 2019)
  • Graduate Excellent Award (Nov. 2016, Jan. 2018)
  • Graduate Travel Award (Nov. 2020)
  • CIRMMT Travel Award (July 2017, Mar. 2018, Mar. 2019, Mar. 2020)
  • CIRMMT Student Award (Mar. 2018, Mar. 2020)
  • International Society for Music Information Retrieval Conference Paper Reviewer (2020–2023, best reviewer in 2021)
  • International Society for Music Information Retrieval Conference Event Coordinator (Sep. 2020)
  • CIRMMT Student Representatives for Research Axis 2 (Music Information Retrieval) (2017–2021)
  • Annual Research Assistant Stipend (2016–2020)
  • Fonds de Recherche du Québec-Société et Culture (FRQSC) Doctoral Scholarship (2018–2022)

Peer-Reviewed Academic Conference Publications

• Ju, Yaolong, Chun Yat Wu, Betty Cortiñas Lorenzo, Jing Yang, Jiajun Deng, Fan Fan, and Simon Lui. End-to-end automatic singing skill evaluation using cross-attention and data augmentation for solo singing and singing with accompaniment. In Proceedings of the 25th International Society for Music Information Retrieval Conference (ISMIR), pp. 493-500, 2024.

• Deng, Jiajun, Yaolong Ju, Jing Yang, Simon Lui, and Xunying Liu. Efficient Adapter Tuning for Joint Singing Voice Beat and Downbeat Tracking with Self-supervised Learning Features. In Proceedings of the 25th International Society for Music Information Retrieval Conference (ISMIR), pp. 343-351, 2024.

• Wu, Yulun, Yaolong Ju, Simon Lui, Jing Yang, Fan Fan, Xuhao Du. Cycle Frequency-Harmonic-Time Transformer for note-level singing voice transcription. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), pp. 1-6, 2024.

• Zhiwei Lin, Jun Chen, Boshi Tang, Binzhu Sha, Jing Yang, Yaolong Ju, Fan Fan, Shiyin Kang, Zhiyong Wu, Helen Meng. Multi-view MidiVAE: Fusing Track-and Bar-view Representations for Long Multi-track Symbolic Music Generation. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 941-945, 2024.

• Yaolong Ju, Chunyang Xu, Yichen Guo, Jinhu Li, and Simon Lui. Improving Automatic Singing Skill Evaluation with Timbral Features, Attention, and Singing Voice Separation. In IEEE International Conference on Multimedia and Expo (ICME), pp. 612-617, 2023.

• Li, Chenyi, Yi Li, Xuhao Du, Yaolong Ju, Shichao Hu, and Zhiyong Wu. VocEmb4SVS: Improving Singing Voice Separation with Vocal Embeddings. In 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pp. 234-239. IEEE, 2022.

• Yaolong Ju, Sylvain Margot, Cory McKay, Luke Dahn, and Ichiro Fujinaga. 2020. Automatic Figured Bass Annotation Using the New Bach Chorales Figured Bass Dataset. In Proceedings of the 21th International Society for Music Information Retrieval Conference, 640–646.

• Yaolong Ju, Sylvain Margot, Cory McKay, and Ichiro Fujinaga. 2020. Automatic Chord Labelling: A Figured Bass Approach. In Proceedings of the 7th International Workshop on Digital Libraries for Musicology, 27–31.

• Jacob deGroot-Maggetti, Timothy Raja de Reuse, Laurent Feisthauer, Samuel Howes, Yaolong Ju, Suzuka Kokubu, Sylvain Margot, Néstor Nápoles López, and Finn Upham. (equal contributions) 2020. Data Quality Matters: Iterative Corrections on a Corpus of Mendelssohn String Quartets and Implications for MIR Analysis. In Proceedings of the 21th International Society for Music Information Retrieval Conference, 432–438.

• Yaolong Ju, Samule Howes, Cory McKay, Nathaniel Condit-Schultz, Jorge Calvo-Zaragoza, and Ichiro Fujinaga. 2019. An Interactive Workflow for Generating Chord Labels for Homorhythmic Music in Symbolic Formats. In Proceedings of the 20th International Society for Music Information Retrieval Conference, 862–869.

• Condit-Schultz, Nathaniel, Yaolong Ju, and Ichiro Fujinaga. 2018. A Flexible Approach to Automated Harmonic Analysis: Multiple Annotations of Chorales by Bach AND Praetorius. In Proceedings of the 19th International Society for Music Information Retrieval Conference, 66-73.

• Yaolong Ju, Nathaniel Condit-Schultz, and Ichiro Fujinaga. 2017. Non-chord Tone Identification Using Deep Neural Networks. In Proceedings of the 4th International Workshop on Digital Libraries for Musicology, 13–16. ACM.

• Lan, Huang, Shixian Du, Yu Zhang, Yaolong Ju, and Zhuo Li. K-means initial clustering center optimal algorithm based on Kruskal. Journal of Information and Computational Science 9, no. 9 (2012): 2387-2392.

Peer-Reviewed Academic Conference Presentations (No Proceedings)

• Yaolong Ju, Sylvain Margot, Cory McKay, and Ichiro Fujinaga. 2020. Figured Bass Encodings for Bach Chorales in Various Symbolic Formats: A Case Study. Presented at the Music Encoding Conference.

• Hopkins, Emily, Yaolong Ju, Gustavo Polins Pedro, Cory McKay, Julie Cumming, and Ichiro Fujinaga. 2019. SIMSSA DB: Symbolic Music Discovery and Search. Poster presentation at the 6th International Workshop on Digital Libraries for Musicology.

• Yaolong Ju, Gustavo Polins Pedro, Cory Mckay, Emily Ann Hopkins, Julie Cumming, and Ichiro Fujinaga. 2019. Enabling Music Search and Analysis: A Database for Symbolic Music Files. Presented at the Music Encoding Conference.

• McKay, Cory, Emily Hopkins, Gustavo Polins Pedro, Yaolong Ju, Andrew Kam, Julie Cumming, and Ichiro Fujinaga. 2019. A collaborative symbolic music database for computational research on music. Presented at the Medieval and Renaissance Music Conference.

• Yaolong Ju, and Kate Helsen. 2018. The LMLO goes MEI: An Exercise in Melodic Encoding Translation Presented at the Music Encoding Conference.

• Yaolong Ju, Nathaniel Condit-Schultz, Claire Arthur and Ichiro Fujinaga. 2017. Non-chord Tone Identification Using Deep Neural Networks. Presented as Late Breaking Demo at the 18th International Society for Music Information Retrieval Conference.