Abstract
The human voice has various characteristics, such as, loudness, pitch, speaking rate, etc. This research presents the classification method of human emotions using voice signals transformed using the short-time Fourier transform (STFT). The STFT can know the frequency component at a desired time point which can be verified using three criteria. Using the 1st criteria, that is, the frequency of the maximum sound intensity (MSI), the emotions can be classified into two groups normal/angry and happy. It is impossible to distinguish between the emotions using the 2<SUP>nd</SUP> criteria, which is, the dwell time of the MSI. Using the 3<SUP>rd</SUP> criteria, that is, the onset of the MSI, the two groups normal, and angry/happy are identified. Therefore, the 1<SUP>st</SUP> and 3<SUP>rd</SUP> criteria can be used to classify three emotions. These results can provide valuable insight for future research on the classification of human emotions.
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