TY - GEN
T1 - Sentiment Classification of English and Hindi Music Lyrics Using Supervised Machine Learning Algorithms
AU - Sumith, N.
AU - Wagle, Shruti
AU - Ghosh, Priyanka
AU - Kishore, Karishma
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85141572459&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85141572459&partnerID=8YFLogxK
U2 - 10.1109/ASIANCON55314.2022.9908688
DO - 10.1109/ASIANCON55314.2022.9908688
M3 - Conference contribution
AN - SCOPUS:85141572459
T3 - 2022 2nd Asian Conference on Innovation in Technology, ASIANCON 2022
BT - 2022 2nd Asian Conference on Innovation in Technology, ASIANCON 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd Asian Conference on Innovation in Technology, ASIANCON 2022
Y2 - 26 August 2022 through 28 August 2022
ER -