The Semantic Shapes of Popular Music Lyrics: Graph-Based Representation, Analysis, and Interpretation of Popular Music Lyrics in Semantic Natural Language Embedding Space

Mitsunori Ogihara, Daniel Galarraga, Gang Ren, Tiago Tavares

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Popular music lyrics are usually brief in length yet sophisticated in narrative content, emotional expression, and structural aesthetics. In this paper, we propose a graph-based analysis and interpretation framework for popular music lyrics using the sematic word embedding representation. This framework explores the temporal and structural information in music lyrics, such as word sequential pattern, lyric format pattern, and predominate song forms, to enhance the understanding of the interaction between the semantic and structural properties of music lyrics. Our proposed analysis and interpretation framework provides extensive tools for representing various properties of music lyrics as graph structural elements and then we implemented feature extraction tools for a comprehensive characterization of the lyric graph using graph analysis or complex network methodologies. The empirical studies based on contrasting music genres are then presented to illustrate the usage of the proposed tools and to demonstrate its modeling and analysis capabilities.

Original languageEnglish (US)
Title of host publicationProceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018
EditorsM. Arif Wani, Moamar Sayed-Mouchaweh, Edwin Lughofer, Joao Gama, Mehmed Kantardzic
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1249-1254
Number of pages6
ISBN (Electronic)9781538668047
DOIs
StatePublished - Jan 15 2019
Event17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018 - Orlando, United States
Duration: Dec 17 2018Dec 20 2018

Publication series

NameProceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018

Conference

Conference17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018
CountryUnited States
CityOrlando
Period12/17/1812/20/18

Keywords

  • Music lyrics
  • Music processing
  • Natural language processing
  • Semantics
  • Word embedding

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Safety, Risk, Reliability and Quality
  • Signal Processing
  • Decision Sciences (miscellaneous)

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