Pengenalan Emosi Berdasarkan Suara Menggunakan Algoritma HMM

Penulis

Barlian Henryranu Prasetio, wijaya kurniawan, Mochammad Hannats Hanafi Ichsan

Abstrak

Abstrak

Penelitian ini bertujuan mengenali emosi seseorang melalui ucapan menggunakan algoritma HMM. Sistem dibangun dapat mengenali 3 jenis emosi yaitu marah, bahagia dan  netral. Fitur yang digunakan dalam sistem ini adalah pitch, energi dan formant. Database yang digunakan adalah suara dari rekaman film. Dari hasil obeservasi probabilitas emosi marah sebesar 0.196, bahagia 0.254 dan netral 0.045. Sistem memiliki tingkat akurasi rata-rata sebesar 86.66%. Rata waktu eksekusi sistem dalam mendeteksi dan mengklasifikasikan emosi sebesar 21.6ms.

Kata kunci: suara, emosi, HMM, klasifikasi

Abstract

This research aims to recognize human emotions through voice using HMM algorithm. The system can confirm three types of emotions: anger, happiness and neutrality. The features used in this system are pitch, energy and formant. From the results, the emotional probability of angry is 0.196, happy is 0.254 and neutral is 0.045. Base on testing result, the system has an average accuracy of 86.66% and average execution time of the system in detecting and classifying emotions of 21.6ms.

Keywords: voice, emotion, HMM, classification

Referensi


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DOI: http://dx.doi.org/10.25126/jtiik.201743339