Toward Multi-modal Music Emotion Classification

Authors:
Yi-Hsuan Yang;Yu-Ching Lin;Heng-Tze Cheng;I-Bin Liao;Yeh-Chin Ho;Homer H. Chen
Affiliations:
National Taiwan University,;National Taiwan University,;National Taiwan University,;Telecommunication Laboratories, Chunghwa Telecom,;Telecommunication Laboratories, Chunghwa Telecom,;National Taiwan University,
Venue:
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Year:
2008

Citing 13
Cited 3

Probabilistic latent semantic indexing

Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Machine learning in automated text categorization

ACM Computing Surveys (CSUR)
A tutorial on support vector regression

Statistics and Computing
Early versus late fusion in semantic video analysis

Proceedings of the 13th annual ACM international conference on Multimedia
Natural language processing of lyrics

Proceedings of the 13th annual ACM international conference on Multimedia
Early versus late fusion in semantic video analysis

Proceedings of the 13th annual ACM international conference on Multimedia
Understanding how bloggers feel: recognizing affect in blog posts

CHI '06 Extended Abstracts on Human Factors in Computing Systems
Automatic Affect Recognition Using Natural Language Processing Techniques and Manually Built Affect Lexicon

IEICE - Transactions on Information and Systems
MusicSense: contextual music recommendation using emotional allocation modeling

Proceedings of the 15th international conference on Multimedia
Affect Analysis of Web Forums and Blogs Using Correlation Ensembles

IEEE Transactions on Knowledge and Data Engineering
Short-Text classification based on ICA and LSA

ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
A Regression Approach to Music Emotion Recognition

IEEE Transactions on Audio, Speech, and Language Processing
Automatic mood detection and tracking of music audio signals

IEEE Transactions on Audio, Speech, and Language Processing

Towards a new reading experience via semantic fusion of text and music

Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Machine Recognition of Music Emotion: A Review

ACM Transactions on Intelligent Systems and Technology (TIST)
Lyrics, music, and emotions

EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

Quantified Score

Hi-index	0.00

Visualization

Abstract

The performance of categorical music emotion classification that divides emotion into classes and uses audio features alone for emotion classification has reached a limit due to the presence of a semantic gap between the object feature level and the human cognitive level of emotion perception. Motivated by the fact that lyrics carry rich semantic information of a song, we propose a multi-modal approach to help improve categorical music emotion classification. By exploiting both the audio features and the lyrics of a song, the proposed approach improves the 4-class emotion classification accuracy from 46.6% to 57.1%. The results also show that the incorporation of lyrics significantly enhances the classification accuracy of valence.