Music and Computation

Biography

Satoru Fukayama (深山 覚)is a Senior Researcher at the National Institute of Advanced Industrial Science and Technology (AIST), Japan. He received his Bachelor degree in Earth and Planetary Physics in 2008, and Ph.D. degree in Information Science and Technology in 2013, both from the University of Tokyo. His main interests are in the theory and applications of automated music generation using machine learning. He has received awards including IPSJ Yamashita SIG Research Award, Specially Selected Paper Award and several Best Presentation Awards from the Information Processing Society of Japan.

CV : [pdf]

Google Scholar : [Link]

Selected PUBLICATIONS (Peer-reviewed)

  1. Song2Guitar: A Difficulty-Aware Arrangement System for Generating Guitar Solo Covers from Polyphonic Audio of Popular Music, Shunya Ariga, Satoru Fukayama, Masataka Goto, Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR2017), pp. 568-574, Oct. 2017.
  2. Music Emotion Recognition with adaptive aggregation of Gaussian Process Regressors, Satoru Fukayama, Masataka Goto, Proceedings of the 41st IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE ICASSP2016), pp.71-75, Mar. 2016
  3. Melody harmonisation with interpolated probabilistic models, Stanislaw. Raczynski, Satoru Fukayama, Emmanuel Vincent, Journal of New Music Research, Oct. 2013
  4. Assistance for Novice Users on Creating Songs from Japanese Lyrics, Satoru Fukayama, Daisuke Saito, Shigeki Sagayama, Proceedings of ICMC, pp.441-446, Sep. 2012
  5. An Interactive Music Composition System Based on Autonomous Maintenance of Musical Consistency, Tetsuro Kitahara, Satoru Fukayama, Shigeki Sagayama, Haruhiro Katayose, Noriko Nagata, Proceedings of SMC, Jul. 2011

Peer-reviewed Publications (in English)

2019

  • AIST Dance Video Database: Multi-Genre, Multi-Dancer, and Multi-Camera Database for Dance Information Processing, Shuhei Tsuchida; Satoru Fukayama; Masahiro Hamasaki; Masataka Goto, 20th International Society for Music Information Retrieval Conference (ISMIR 2019), pp. 501-510, Nov. 2019.
  • ABCPRec: Adaptively Bridging Consumer and Producer Roles for User-Generated Content Recommendation, Kosetsu Tsukuda, Satoru Fukayama, Masataka Goto, 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR 2019), pp. 1197-1200, July 2019.
  • Automatic Singing Transcription based on Encoder-Decoder Recurrent Neural Networks with a Weakly-Supervised Attention Mechanism, Ryo Nishikimi, Eita Nakamura, Satoru Fukayama, Masataka Goto, Kazuyoshi Yoshii, 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP2019), pp. 161-165, May 2019.
  • Transdrums: A Drum Pattern Transfer System Preserving Global Pattern Structure, Shun Sawada, Satoru Fukayama, Masataka Goto, Keiji Hirata, 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP2019), pp. 391-395, May 2019.
  • Joint Transcription of Lead, Bass, and Rhythm Guitars based on a Factorial Hidden Semi-Markov Model, Kentaro Shibata, Ryo Nishikimi, Satoru Fukayama, Masataka Goto, Eita Nakamura, Katsutoshi Itoyama, Kazuyoshi Yoshii, 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP2019), pp. 236-240, May 2019.
  • Query-by-Dancing: A Dance Music Retrieval System Based on Body-Motion Similarity, Shuhei Tsuchida, Satoru Fukayama, Masataka Goto, 25th International Conference on MultiMedia Modeling (MMM2019), pp. 251-263, Jan. 2019.
  • Audio-Based Automatic Generation of a Piano Reduction Score by Considering the Musical Structure, Hirofumi Takamori, Takayuki Nakatsuka, Satoru Fukayama, Masataka Goto, Shigeo Morishima, 25th International Conference on MultiMedia Modeling (MMM2019), pp. 169-181, Jan. 2019.

2018

  • Listener Anonymizer: Camouflaging Play Logs to Preserve User’s Demographic Anonymity, Kosetsu Tsukuda, Satoru Fukayama, Masataka Goto, The 19th International Society for Music Information Retrieval Conference (ISMIR 2018), pp. 687-694, Sep. 2018.
  • Instrudive: A Music Visualization System Based on Automatically Recognized Instrumentation, Takumi Takahashi, Satoru Fukayama, Masataka Goto, The 19th International Society for Music Information Retrieval Conference (ISMIR 2018), pp. 561-568, Sep. 2018.
  • Comparing RNN Parameters for Melodic Similarity, Tian Cheng, Satoru Fukayama, Masataka Goto, The 19th International Society for Music Information Retrieval Conference (ISMIR 2018), pp. 763-770, Sep. 2018.
  • Convolving Gaussian Kernels for RNN-based Beat Tracking, Tian Cheng, Satoru Fukayama, Masataka Goto, The 26th European Signal Processing Conference (EUSIPCO 2018), pp. 1919-1923, Sep. 2018.
  • ChordScanner: Browsing Chord Progressions based on Musical Typicality and Intra-Composer Consistency, Hiromi Nakamura, Tomoyasu Nakano, Satoru Fukayama, Masataka Goto, The 43rd International Computer Music Conference (ICMC 2018), pp. 250-255, Aug. 2018.
  • CTcomposer: An Interface for Music Composition Considering Intra-Composer Consistency and Musical Typicality, Hiromi Nakamura, Tomoyasu Nakano, Satoru Fukayama, Masataka Goto, The 15th Sound and Music Computing Conference (SMC 2018), pp. 500-507, Jul. 2018.
  • A Melody-conditioned Lyrics Language Model, Kento Watanabe, Yuichiroh Matsubayashi, Satoru Fukayama, Masataka Goto, Kentaro Inui, Tomoyasu Nakano, Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018), pp. 163-172, June 2018.
  • Modeling Storylines in Lyrics, Kento watanabe, Yuichiroh Matsubayashi, Kentaro Inui, Satoru Fukayama, Tomoyasu Nakano, Masataka Goto, IEICE Transaction on Information and Systems, Vol. E101.D, No. 4, pp. 1167-1179, 2018.

2017

2016

2015

2014

2013

2012

2011

2010

2009