JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Vol 1 No 2 (2017)

Analisis Koefisien Cepstral Emosi Berdasarkan Suara

Mohidin, Ismail (Unknown)
Tupamahu, Frangky (Unknown)



Article Info

Publish Date
30 Dec 2017

Abstract

Abstract - The speech signal carries some sort of information, which consists of the intent to be conveyed, who speaks the information, and the emotional information that shows the emotional state of the utterance. One of the characteristics of human voice is the fundamental frequency. In this study the selection of features and methods of classification and recognition is important to recognize the emotional level (anger, sadness, fear, pleasure and neutral) contained in the dataset, this research proposes design through two main processes of training and introduction recognition). Experiments conducted using the Indonesian emotion voice dataset and the Mel-Frequency Cepstrum Coefficients (MFCC) algorithm were used to extract features from sound emotion. MFCC produces 13 cepstral coefficients of each of the sound emotion signals. This coefficient is used as an input of classification of emotional data from 250 data sampling.

Copyrights © 2017






Journal Info

Abbrev

JAIC

Publisher

Subject

Computer Science & IT

Description

Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan ...