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Music Mood Categorization: A Survey

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ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management (ICICCT 2019)

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Abstract

Music is one among the many emotion rich resources because of which it is very much common for music listeners to maintain music libraries in terms of mood. The growing availability of online music data and their vast applications have resulted in steady increase of interest among music researchers to move towards automatic music mood classification. A substantial amount of work has been reported on this task for western languages compared to Indian languages. Standard linguistic resources like WordNet and dictionaries are available for western languages. Due to scarcity of such resources not much work has been carried out for Indian languages. The central objective of this paper is to present a survey related to various existing music mood taxonomies, highlight different modalities considered for music mood classification and to discuss various techniques and systems with due focus on open challenges.

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Author information

Authors and Affiliations

  1. Jawaharlal Nehru Technological University Hyderabad (JNTUH), Hyderabad, India

    Tula Vandana

  2. G. Narayanamma Institute of Technology and Science (GNITS), Hyderabad, India

    Tula Vandana & Nara Kalyani

  3. School of Information Technology (SIT), JNTUH, Hyderabad, India

    K. Santhi Sree

Authors
  1. Tula Vandana
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  2. Nara Kalyani
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  3. K. Santhi Sree
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Corresponding authors

Correspondence to Tula Vandana or Nara Kalyani .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, CMR Institute of Technology, Hyderabad, Telangana, India

    Vinit Kumar Gunjan

  2. Department of Computer Science, University of Oviedo, Oviedo, Spain

    Vicente Garcia Diaz

  3. Faculty of Engineering, Don Bosco University, San Salvador, El Salvador

    Manuel Cardona

  4. Department of Computer Science and Engineering, CMR Institute of Technology (Autonomous), Hyderabad, Telangana, India

    Vijender Kumar Solanki

  5. BVRIT Hyderabad College of Engineering for Women, Hyderabad, Telangana, India

    K. V. N. Sunitha

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Vandana, T., Kalyani, N., Santhi Sree, K. (2020). Music Mood Categorization: A Survey. In: Gunjan, V., Garcia Diaz, V., Cardona, M., Solanki, V., Sunitha, K. (eds) ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management. ICICCT 2019. Springer, Singapore. https://doi.org/10.1007/978-981-13-8461-5_14

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  • DOI: https://doi.org/10.1007/978-981-13-8461-5_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-8460-8

  • Online ISBN: 978-981-13-8461-5

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