Pengenalan Emosi Manusia Berbasis Data Suara Menggunakan Algoritma Backpropagation - Muhammad Iqbal G Putra; Andrew Brian Osmond; Casi Setianingsih (eProceedings of Engineering, 2018)
Abstract The current technological developments are growing very fast and have enormous benefits on our lives. To examine more about how a computer recognizes emotions in humans through the sound media that is processed first and adjust the computer language or in other words Emotion Recognition. This final project uses Neural Network method. Neural Network or also called in bahasa is Jaringan Syaraf Tiruan (JST) is an effective system that can change its structure based on flowing information. Neural Network in this final project is used to conduct training and data testing. While Fast Fourier transform (FFT) is used to process sound data and convert from analog to digital, which is used as input of Neural Network and processed asone of the materials to get the decision whether the voice data used contain emotion or the system cannot detect the emotion. So after the authors do the test system that has been made obtained 100% accuracy on the test of cross validation, this result shows that the system is very good for use in detecting emotion in a voice. While the test using Indonesian language test data system get 79.1667% accuracy and the test using the English language test data accuracy obtained for 89.1892%, it shows that the system is made better use of English test data because the data train on the system using data practicing english speaking. Keywords : Emotion Recognition, Neural Network, Jaringan Saraf Tiruan, FFT.