Skip to main content

Mood Tracking of Musical Compositions

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7661))

Abstract

This paper presents a new strategy for the analysis of emotions contained within musical compositions. We present a method for tracking changing emotions during the course of a musical piece. The collected data allowed to determine the dominant emotion in the musical composition, present emotion histograms and construct maps visualizing the distribution of emotions in time. The amount of changes of emotions during a piece may be different, therefore we introduced a parameter evaluating the quantity of changes of emotions in a musical composition. The information obtained about the emotion in a piece made it possible to analyze a number of pieces, in particular the Sonatas of Ludwig van Beethoven. This analysis has provided new knowledge about the compositions and the method of their emotional development.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Pratt, C.C.: Music as the language of emotion. The Library of Congress (1950)

    Google Scholar 

  2. Lu, L., Liu, D., Zhang, H.J.: Automatic mood detection and tracking of music audio signals. IEEE Transactions on Audio, Speech and Language Processing 14(1), 5–18 (2006)

    Article  MathSciNet  Google Scholar 

  3. Schmidt, E.M., Turnbull, D., Kim, Y.E.: Feature Selection for Content-Based, Time-Varying Musical Emotion Regression. In: Proc. ACM SIGMM International Conference on Multimedia Information Retrieval, Philadelphia, PA (2010)

    Google Scholar 

  4. Schmidt, E.M., Kim, Y.E.: Prediction of time-varying musical mood distributions from audio. In: Proceedings of the 2010 International Society for Music Information Retrieval Conference, Utrecht, Netherlands (2010)

    Google Scholar 

  5. Myint, E.E.P., Pwint, M.: An approach for multi-label music mood classification. In: 2nd International Conference on Signal Processing Systems, ICSPS (2010)

    Google Scholar 

  6. Grekow, J., Raś, Z.W.: Emotion Based MIDI Files Retrieval System. In: Raś, Z.W., Wieczorkowska, A.A. (eds.) Advances in Music Information Retrieval. SCI, vol. 274, pp. 261–284. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  7. Mohammad, S.: From Once Upon a Time to Happily Ever After: Tracking Emotions in Novels and Fairy Tales. In: Proceedings of the ACL 2011 Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, Portland, OR, USA, pp. 105–114 (2011)

    Google Scholar 

  8. Yeh, J.-H., Pao, T.-L., Pai, C.-Y., Cheng, Y.-M.: Tracking and Visualizing the Changes of Mandarin Emotional Expression. In: Huang, D.-S., Wunsch II, D.C., Levine, D.S., Jo, K.-H. (eds.) ICIC 2008. LNCS, vol. 5226, pp. 978–984. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  9. Grekow, J., Raś, Z.W.: Detecting Emotions in Classical Music from MIDI Files. In: Rauch, J., Raś, Z.W., Berka, P., Elomaa, T. (eds.) ISMIS 2009. LNCS (LNAI), vol. 5722, pp. 261–270. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  10. Thayer, R.E.: The biopsychology arousal. Oxford University Press (1989)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Grekow, J. (2012). Mood Tracking of Musical Compositions. In: Chen, L., Felfernig, A., Liu, J., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2012. Lecture Notes in Computer Science(), vol 7661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34624-8_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34624-8_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34623-1

  • Online ISBN: 978-3-642-34624-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics