A4 Article in conference proceedings
Musical Feature and Novelty Curve Characterizations as Predictors of Segmentation Accuracy (2017)

Hartmann, M., Lartillot, O., & Toiviainen, P. (2017). Musical Feature and Novelty Curve Characterizations as Predictors of Segmentation Accuracy. In T. Lokki, J. Pätynen, & V. Välimäki (Eds.), SMC 2017 : Proceedings of the 14th Sound and Music Computing Conference 2017 (pp. 365-372). Aalto-yliopisto. Proceedings of the Sound and Music Computing Conferences. http://smc2017.aalto.fi/

JYU authors or editors

Publication details

All authors or editors: Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

Parent publication: SMC 2017 : Proceedings of the 14th Sound and Music Computing Conference 2017

Parent publication editors: Lokki, Tapio; Pätynen, Jukka; Välimäki, Vesa

ISBN: 978-952-60-3729-5

Journal or series: Proceedings of the Sound and Music Computing Conferences

ISSN: 2518-3672

eISSN: 2518-3672

Publication year: 2017

Pages range: 365-372

Publisher: Aalto-yliopisto

Place of Publication: Helsinki

Publication country: Finland

Publication language: English

Persistent website address: http://smc2017.aalto.fi/

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/54912

Additional information: 14th Sound and Music Computing Conference 2017. July 5-8 2017, Espoo, Finland.

Keywords: music; predictability; rhythm; keys (tone systems)

Free keywords: notation (music); novelty detection; novelty curves; musical features

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2017

JUFO rating: 1