M
Masataka Goto
Researcher at National Institute of Advanced Industrial Science and Technology
Publications - 327
Citations - 9603
Masataka Goto is an academic researcher from National Institute of Advanced Industrial Science and Technology. The author has contributed to research in topics: Audio signal & Singing. The author has an hindex of 48, co-authored 316 publications receiving 8944 citations. Previous affiliations of Masataka Goto include University of Wollongong & Nippon Telegraph and Telephone.
Papers
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Journal ArticleDOI
Content-Based Music Information Retrieval: Current Directions and Future Challenges
Michael A. Casey,Remco C. Veltkamp,Masataka Goto,Marc Leman,Christophe Rhodes,Malcolm Slaney +5 more
TL;DR: In this paper, the authors outline the problems of content-based music information retrieval and explore the state-of-the-art methods using audio cues (e.g., query by humming, audio fingerprinting, contentbased music retrieval) and other cues such as music notation and symbolic representation.
Proceedings Article
RWC Music Database: Popular, Classical, and Jazz Music Databases
TL;DR: The design policy and specifications of the RWC Music Database are described, a music database (DB) that is available to researchers for common use and research purposes, which contains four original DBs: the Popular Music Database (100 pieces), Royalty-Free Music Database(15 pieces), Classical Music Database ($50 pieces), and Jazz Music Database (£50 pieces).
Proceedings Article
RWC Music Database: Music Genre Database and Musical Instrument Sound Database
TL;DR: The design policy and specifications of the RWC Music Database, a copyright-cleared music database compiled specifically for research purposes, are described and it is hoped that the DB will make a significant contribution to future advances in the field of music information processing.
Journal ArticleDOI
A real-time music-scene-description system: predominant-F0 estimation for detecting melody and bass lines in real-world audio signals
TL;DR: A predominant-F0 estimation method called PreFEst is proposed that does not rely on the unreliable fundamental component and obtains the most predominant F0 supported by harmonics within an intentionally limited frequency range.
Journal ArticleDOI
An Audio-based Real-time Beat Tracking System for Music With or Without Drum-sounds
TL;DR: A real-time beat tracking system that recognizes a hierarchical beat structure comprising the quarter-note, half- note, and measure levels in real-world audio signals sampled from popular-music compact discs is described.