A Classification Study on the Emotional Recognition Based on the Speech Signals Using STFT
Young-ha Shin, Kyu Ye Song, Channyeong Yun, Woo‐Jin Cho, Hyung-Joo Park, Dong-Young Jang · Journal of the korean society of manufacturing technology engineers · 2021
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 2nd criteria, which is, the dwell time of the MSI. Using the 3rd criteria, that is, the onset of the MSI, the two groups normal, and angry/happy are identified. Therefore, the 1st and 3rd criteria can be used to classify three emotions. These results can provide valuable insight for future research on the classification of human emotions.