Pengenalan Pola Emosi Manusia Berdasarkan Ucapan Menggunakan Ekstraksi Fitur Mel-Frequency Cepstral Coefficients (MFCC) - Siti Helmiyah; Abdul Fadlil; Anton Yudhana (Fakultas Ilmu Komputer, Universitas Klabat, 2018)
Human emotion recognition subject becomes important due to it's usability in daily lifestyle which requires human and computer interraction. Human emotion recognition is a complex problem due to the difference within custom tradition and specific dialect which exists on different ethnic, region and community. This problem also exacerbated due to objectivity assessment for the emotion is difficult since emotion happens unconsciously. This research conducts an experiment to discover pattern of emotion based on feature extracted from speech. Method used for feature extraction on this experiment is Mel-Frequency Cepstral Coefficient (MFCC) which is a method that similar to the human hearing system. Dataset used on this experiment is Berlin Database of Emotional Speech (Emo-DB). Emotions that are used for this experiments are happiness, boredom, neutral, sad and anger. For each of these emotion, 3 samples from Emo-DB are taken as experimental subject. The emotion patterns are successfully visible using specific values for MFCC parameters such as 25 for frame duration, 10 for frame shift, 0.97 for preemphasis coefficient, 20 for filterbank channel and 12 for ceptral coefficients. MFCC features are then extracted and calculated to find mean values from these parameters. These mean values are then plotted based on timeframe graph to be investigated to find the specific pattern which appears from each emotion. Keywords— Emotion, Speech, Mel-Frequency Cepstral Coefficients (MFCC).