Abstract
Because music is not objectively descriptive or representational, the subjective qualities of music seem to be most important. Style is one of the most salient qualities of music, and in fact most descriptions of music refer to some aspect of musical style. Style in music can refer to historical periods, composers, performers, sonic texture, emotion, and genre. In recent years, many aspects of music style have been studied from the standpoint of automation: How can musical style be recognized and synthesized? An introduction to musical style describes ways in which style is characterized by composers and music theorists. Examples are then given where musical style is the focal point for computer models of music analysis and music generation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Alamkan C, Birmingham B, Simoni M (1999) Stylistic structures: an initial investigation of the stochastic generation of tonal music. University of Michigan, Technical Report CSE-TR-395–99
Berenzweig A, Logan B, Ellis D, Whitman B (2004) A large-scale evaluation of acoustic and subjective music similarity measures. Comput Music J 28(2):63–76
Bresin R, Friberg A (2000) Emotional coloring of computer-controlled music performance. Comput Music J 24(4):44–62
Cope D (1991) Computers and musical style. (The computer music and digital audio series, 6.) A-R Editions, Middleton, WI
Dannenberg RB, Thom B, Watson D (1997) A machine learning approach to musical style recognition. In: 1997 international computer music conference. International computer music association, San Francisco, CA, pp 344–347
Dixon S, Pampalk E, Widmer G (2003) Classification of dance music by periodicity patterns. In: 4th international conference on music information retrieval (ISMIR 2003), Baltimore, MD, pp 159–165
Juslin PN, Sloboda JA (2001) Music and emotion. Oxford University Press, London
Magno T, Sable C (2008) A comparison of signal-based music recommendation to genre labels, collaborative filtering, musicological analysis, human recommendation, and random baseline. In: ISMIR 2008, Proceedings of the 9th international conference on music information retrieval, Philadelphia, PA, pp 161–166
Merriam-Webster (2007) Merriam-Webster Online. http://www.m-w.com/dictionary/style. Accessed 26 Nov 2008
Mitchell T (1997) Machine learning. McGraw Hill, New York
Pauws S, Eggen B (2002) PATS: realization and user evaluation of an automatic playlist generator. In: Proceedings of the 3rd international conference on music information retrieval (ISMIR’02), Paris, pp 222–230
Perrot D, Gjerdigen R (1999) Scanning the dial: an exploration of factors in identification of musical style (abstract only). In: Proceedings of the society for music perception and cognition, Evanston, IL, p 88
Rothstein J (1995) MIDI: a comprehensive introduction, 2nd edn. A-R Editions, Middleton, WI
Sadie S, Tyrell J (2001) The new grove dictionary of music and musicians, 2nd edn. Oxford University Press, Oxford
Sundberg J (1988) Computer synthesis of music performance. In: Sloboda JA (ed) Generative processes in music. The psychology of performance, improvisation, and composition. Clarenden, Oxford, pp 52–69
Torrens M, Hertzog P, Arcos JL (2004) Visualizing and exploring personal music libraries. In: 5th international conference on music information retrieval, Barcelona, pp 421–424
Tzanetakis G, Cook P (2002) Musical genre classification of audio signals. IEEE Trans Speech Audio Process 10(5):293–302
Woods WA (1970) Transition network grammars for natural language analysis. Commun ACM 13(10):591–606
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Dannenberg, R.B. (2010). Style in Music. In: Argamon, S., Burns, K., Dubnov, S. (eds) The Structure of Style. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12337-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-12337-5_3
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12336-8
Online ISBN: 978-3-642-12337-5
eBook Packages: Computer ScienceComputer Science (R0)