International Journal of Scientific and Research Publications

IJSRP, Volume 5, Issue 11, November 2015 Edition [ISSN 2250-3153]


Study of Emotion Detection in Tunes Using Machine Learning
      Rishika Shetty, Shweta Kasbe, Kimaya Jorwekar, Dharti Kamble, Prof. Makarand Velankar
Abstract: The main objective of this paper is to study possible emotions generation in listener’s mind due to listening of tunes. Such emotions can be detected automatically using the audio features such as zero crossing, compactness, spectral centroid, spectral Flux, spectrum Roll off and Beat Histogram etc. We have explored machine Learning algorithms such as SVM (support vector machine) and ANN (Artificial Neural Network) for classification. The proposed technique of emotion detection is done in two parts as feature extraction and classification of tunes using machine learning techniques. We have studied different tools for extracting the features of tunes. These extracted features can be further given to the classifiers to categorize the emotions.

Reference this Research Paper (copy & paste below code):

Rishika Shetty, Shweta Kasbe, Kimaya Jorwekar, Dharti Kamble, Prof. Makarand Velankar (2018); Study of Emotion Detection in Tunes Using Machine Learning; Int J Sci Res Publ 5(11) (ISSN: 2250-3153). http://www.ijsrp.org/research-paper-1115.php?rp=P474811
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