Music Classification Based On Mood Recognition
| Author(s) | : | Patel Dhruja D |
| Institution | : | Information Technology Department, Parul Institute of Engineering and Technology,Waghodia, Vadodara, India. |
| Published In | : | Vol. 4, Issue 3 — March 2017 |
| Page No. | : | 166-168 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Music emotion is a vital component in the field of multimedia database recovery andcomputational musicology. The online musical datasets are major challenges for searching, retrieving,and organizing the music content. Therefore, there is a require for robust automatic music emotionclassifier system for organizing variety music pieces into different classes according to the specificviable information. Basic components are to be considered for music emotion classification audio featureo r i g i n and classifier design. In user propose diverse audio features to precisely characterize the musicsubstance. The feature sets belong to groups dynamic, rhythmic, spectral, and harmonic. Four statisticalparameters are considered as representatives, including the fourth-order central moments of eachfeature as well as covariance part. Number of unimportant parameters is forced by minimum unemploymentmaximum relevance(MRMR)algorithm and principal component analysis(PCA). Support VectorMachine(SVM) is used as a classifiers to classify the music mood recognition.
Patel Dhruja D, “Music Classification Based On Mood Recognition”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 3, pp. 166-168, March 2017.
