kumoh national institute of technology
Networked Systems Lab.

Alifia Putri Anantha, Philip Tobianto Daely, Jae Min Lee, and Dong Seong Kim, "Hidden Information Detection in Speech Signal Using MFCC and LDA", 2020 Korean Institute of Communication and Sciences (KICS) Summer Conference, August 12-14, 2020, Yong Pyong Resort, Pyeongchang, Gangwon Province, Korea (N12)
By : Alifia Putri Anantha
Date : 2020-06-08
Views : 133

In this research, it has been done a system that can steganalize a wav format speech file by analyzing the values or characteristics of the speech signal. In order to know the characteristics itself, Mel-Frequency Cepstral Coefficient (MFCC) method is used here to extract the features of the speech signals and Linear Discriminant Analysis (LDA) method is used to do the features selection. Support Vector Machine (SVM) is used for the classification process. The final output of this system is a condition that states the speech signal is original, contains hidden message, or contains noise.