Music and Audio Computing Lab

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Singing Voice Analysis

Singing voice is the central sound source that determines the song quality, as it conveys melody, lyrics, emotion and humanity with its high expressivity. In this research subject, we investigate various methods to analyze different characteristics of singing voice in popular music.


all together

K-pop Vocal Tagging System


We have worked on several sub-topics including singing voice detection, Melodic Pitch Estimation, singer identification and tagging. Here are the lists of categorized publications.


Singing Voice Detection and Melodic Pitch Estimation

  • Semi-Supervised Learning Using Teacher-Student Models for Vocal Melody Extraction
    Sangeun Kum, Jing-Hua Lin, Li Su, and Juhan Nam
    Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR), 2020 (accepted)
  • Joint Detection and Classification of Singing Voice Melody Using Convolutional Recurrent Neural Networks
    Sangeun Kum and Juhan Nam
    Applied Sciences, 2019 [pdf] [code]
  • Revisiting Singing Voice Detection: a Quantitative Review and the Future Outlook
    Kyungyun Lee, Keunwoo Choi and Juhan Nam
    Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), 2018 [pdf] [code]
  • Melody Extraction on Vocal Segments Using Multi-Column Deep Neural Networks
    Sangeun Kum, Changheun Oh and Juhan Nam
    Proceedings of International Society for Music Information Retrieval Conference (ISMIR), 2016 [pdf] [website]

Singer Identification, Timbre and Style Analysis

  • Semantic Tagging of Singing Voices in Popular Music Recordings
    Keunhyoung Luke Kim, Jongpil Lee, Sangeun Kum, Chae Lin Park, and Juhan Nam
    IEEE/ACM Transactions on Audio, Speech and Language Processing, 2020 [pdf] [website/dataset]
  • Learning a Joint Embedding Space of Monophonic and Mixed Music Signals for Singing Voice
    Kyungyun Lee and Juhan Nam
    Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), 2019 [pdf] [website] [code]
  • A Hybrid of Deep Audio Feature and i-vector for Artist Recognition
    Jiyoung Park, Donghyun Kim, Jongpil Lee, Sangeun Kum and Juhan Nam
    Joint Workshop on Machine Learning for Music, International Conference on Machine Learning (ICML), 2018 [pdf]
  • Building K-POP Singing Voice Tag Dataset: A Progress Report
    KeunHyoung Luke Kim, Sangeun Kum, Chae Lin Park, Jongpil Lee, Jiyoung Park and Juhan Nam
    Late Breaking Demo in the 18th International Society for Musical Information Retrieval Conference (ISMIR), 2017 [pdf]


Funding

We have received the following funds to support this research.

  • Naver - industry research fund, 2017-2019
  • National Research Foundation of Korea, 2015-2018