Deni Ardiansyah, . (2021) MODEL KLASIFIKASI EMOSI BERDASARKAN SUARA DENGAN METODE MULTILAYER PERCEPTRON. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Human-computer interaction technology has developed, for example, speech recognition. One of the uses of speech recognition is to recognize human emotions. Computers can recognize and classify human emotions based on sound. There have been many studies related to various method of feature extraction and classification but the results are still not close to perfect. The feature extraction method uses the Mel Frequency Ceptral Coefficient (MFCC). The data used is secondary data sourced from the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS). The system model will be able to recognize 8 types of emotions, namely neutral, calm, happy, sad, angry, scared, disgusted and surprised. The results of the model obtained accuracy for neutral emotions by 98%, calm emotions by 97%, happy emotions by 94%, sad emotions by 97%, angry emotions by 97%, fearful emotions by 94%, disgust emotions by 97% and shocking emotions. by 96%. So that the results of the average accuracy of the models that have been made are 96%.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | No.Panggil : 1610511029 Pembimbing 1 : Jayanta Pembimbing 2 : Yuni Widiastiwi Penguji 1 : Henki Bayu Seta Penguji 2 : Nurul Chamidah |
| Uncontrolled Keywords: | Speech Recognition, Emotion, Sound, Classification, Multilayer Perceptron |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Deni Ardiyansyah |
| Date Deposited: | 06 Apr 2021 07:41 |
| Last Modified: | 06 Apr 2021 07:41 |
| URI: | http://repository.upnvj.ac.id/id/eprint/9307 |
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