Sentiment Classification of English and Hindi Music Lyrics Using Supervised Machine Learning Algorithms

N. Sumith, Shruti Wagle, Priyanka Ghosh, Karishma Kishore

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

Abstract

Finding music based on one's mood is difficult unless it is manually classified and separated into distinct playlists. This is especially tough when the song is not in English due to varying lexical and syntactic styles. Our project employs textual sentiment analysis by testing various binary classifier algorithms - Random Forest, Naive Bayes, Support Vector Machine (SVM), and AdaBoost - to gauge which method is best for classifying English and Hindi language music lyrics into positive (happy) and negative (sad) sentiment.

Original languageEnglish
Title of host publication2022 2nd Asian Conference on Innovation in Technology, ASIANCON 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665468510
DOIs
Publication statusPublished - 2022
Event2nd Asian Conference on Innovation in Technology, ASIANCON 2022 - Ravet, India
Duration: 26-08-202228-08-2022

Publication series

Name2022 2nd Asian Conference on Innovation in Technology, ASIANCON 2022

Conference

Conference2nd Asian Conference on Innovation in Technology, ASIANCON 2022
Country/TerritoryIndia
CityRavet
Period26-08-2228-08-22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Health Informatics

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