MUSA2004 Music Information Research (5 op)
Kuvaus
The course provides an overview of main areas and methodologies in computational analysis of music, including signal processing and feature extraction, machine learning, and semantic computing.
Osaamistavoitteet
After completing the course the student will:
· be able to program in computer languages relevant to Music Information Research (e.g. MATLAB)
· understand the processes involved in computational musical feature extraction (e.g. extract from a digital audio signal information related to pitch, timbre, rhythm, meter, tonality)
· understand and implement methods for music classification, segmentation
· understand methods of semantic computing, and/or is able to retrieve large data using music APIs
Lisätietoja
Toinen tai kolmas opintovuosi
Oppimateriaalit
Eerola, T. & Toiviainen, P. (2004). MIDI Toolbox: MATLAB Tools for Music Research. University of Jyväskylä: Kopijyvä, Jyväskylä, Finland.
O. Lartillot, MIRtoolbox 1.8.2 User’s Manual,, University of Oslo, Norway RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion www.jyu.fi/music/coe/materials/mirtoolbox
Schedl M, Gómez E, Urbano J. Music information retrieval: recent developments and applications. Foundations and Trends in Information Retrieval. 2014 Sept 12; 8 (2-3): 127-261. DOI: 10.1561/1500000042 https://repositori.upf.edu/handle/10230/27565
Kirjallisuus
- Eerola, T. & Toiviainen, P. (2004). MIDI Toolbox: MATLAB Tools for Music Research. University of Jyväskylä: Kopijyvä, Jyväskylä, Finland.
- O. Lartillot, MIRtoolbox 1.8.2 User’s Manual,, University of Oslo, Norway RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion
- Schedl M, Gómez E, Urbano J. Music information retrieval: recent developments and applications. Foundations and Trends in Information Retrieval. 2014 Sept 12; 8 (2-3): 127-261. DOI: 10.1561/1500000042