Classification of Emotion with Audio Analysis

Authors : Coşkucan BÜYÜKYILDIZ, Ismail SARITAS, Ali YAŞAR

Pages : 467-481

Doi:10.53433/yyufbed.1219879

View : 54 | Download : 48

Publication Date : 2023-08-31

Article Type : Research Paper

Abstract :Classification is an important technique used to distinguish data samples. The aim of this study is to classify according to emotions by extracting audio features. Two male and two female individuals expressed four different emotions as \`fun\`, \`angry\`, \`neutral\` and \`sleepy\` in the voice data. We used to “MFCC” as a Cepstral feature, “Centroid, Flatness, Skewness, Crest, Flux, Slope, Decrease, Kurtosis, Spread, Entropy, roll off point” as Spectral Feature, “Pitch, Harmonic ratio” as Periodicity Features in the sound features. After, we applied to the data that all the classification algorithms located in the classification learner toolbox in Matlab and we tried to classify the emotion with the algorithm that provides the highest accuracy. Each data in the classification study has twenty-six features inputs and one labeled output value. According to the results, support vector machine algorithm provided the highest accuracy performance. Considering the performances obtained, this study reveals that it is possible to distinguish and classify sounds using sentimental data and sound feature parameters.
Keywords : Destek Vektör Makinesi, Duygu Tanımlama, Makine Öğrenmesi Veritabanı, Ses Öznitelikleri, Sınıflandırma