Multimodal Mood Classification Framework for Hindi Songs

Authors

  • Braja Gopal Patra Jadavpur University
  • Dipankar Das Jadavpur University
  • Sivaji Bandyopadhyay Jadavpur University

DOI:

https://doi.org/10.13053/cys-20-3-2461

Keywords:

Hindi songs, mood classification, multimodal dataset, mood taxonomy, audio, lyrics.

Abstract

Music information retrieval is currently an active domain of research. An interesting aspect of music information retrieval involves mood classification. While the Western music captured much attention, research on Indian music was limited and mostly based on audio data. In this work, the authors propose a mood taxonomy and describe the framework for developing a multimodal dataset (audio and lyrics) for Hindi songs. We observed differences in mood for several instances of Hindi songs while annotating the audio of such songs in contrast to their corresponding lyrics. Finally, the mood classification frameworks were developed for Hindi songs and they consist of three different systems based on the features of audio, lyrics and both. The mood classification systems based on audio and lyrics achieved F-measures of 58.2% and 55.1%, respectively whereas the multimodal system (combination of both audio and lyrics) achieved the maximum F-measure of 68.6%.

Author Biographies

Braja Gopal Patra, Jadavpur University

Is a Ph.D. Scholar in the Department of Computer Science and Engineering, Jadavpur University, India. He received Master’s degree from the Department of Computer Science and Engineering, National Institute of Technology (NIT), Agartala, India in 2012 and Bachelor’s degree in Computer Science and Engineering from West Bengal University of Technology, India in 2010. He is a recipient of the Visvesvaraya Ph.D. fellowship of “Department of Electronics and Information Technology”, Government of India. His research interests include Music Information Retrieval, Sentiment Analysis, and Natural Language Processing. He is a member of the ACL and IEEE.

Dipankar Das, Jadavpur University

Is an Assistant Professor in the Department of Computer Science and Engineering, Jadavpur University, India. He received Ph.D. and Master’s degrees from the Department of Computer Science and Engineering, Jadavpur University in 2013 and 2009 respectively. He received Bachelor’s degree in Computer Science and Engineering from West Bengal University of Technology in 2005. His research interests are in the area of Natural Language Processing, Emotion and Sentiment Analysis, Affect Computing, Information Extraction and Language Generation. He has more than 50 publications in top conferences and journals and has served as an author over 15 Book Chapters. He is a member of the IEEE, ACL, HUMAINE groups.

Sivaji Bandyopadhyay, Jadavpur University

Is a Professor in the Department of Computer Science and Engineering, Jadavpur University, India. He received the Ph.D., Master’s and Bachelor’s degrees from the Department of Computer Science and Engineering, Jadavpur University in 1998, 1987, and 1985, respectively. He is engaged with several national and international projects. His research interests are in the area of Natural Language Processing, Machine Learning, Machine Translation, Sentiment Analysis, Question Answering Systems and Information Extraction. He has more than 300 publications in top conferences and journals. He has served as program chair, workshop chair and PC member of COLING, IJCNLP, NAACL, NLPKE, ICON and others. He is a member of the ACL, AAMT.

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Published

2016-09-30

Issue

Vol. 20 No. 3 (2016): Thematic Issue: Natural Language Processing and Computational Linguistics (Guest Editor: Alexander Gelbukh)

Section

Articles

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