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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Mohamad Helmy Ramlan
ASE Electronics (M) Sdn. Bhd.

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Fuzzy-based voiced-unvoiced segmentation for emotion recognition using spectral feature fusions Yusnita Mohd Ali; Alhan Farhanah Abd Rahim; Emilia Noorsal; Zuhaila Mat Yassin; Nor Fadzilah Mokhtar; Mohamad Helmy Ramlan
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp196-206

Abstract

Despite abundant growth in automatic emotion recognition system (ERS) studies using various techniques in feature extractions and classifiers, scarce sources found to improve the system via pre-processing techniques. This paper proposed a smart pre-processing stage using fuzzy logic inference system (FIS) based on Mamdani engine and simple time-based features i.e. zero-crossing rate (ZCR) and short-time energy (STE) to initially identify a frame as voiced (V) or unvoiced (UV). Mel-frequency cepstral coefficients (MFCC) and linear prediction coefficients (LPC) were tested with K-nearest neighbours (KNN) classifiers to evaluate the proposed FIS V-UV segmentation. We also introduced two feature fusions of MFCC and LPC with formants to obtain better performance. Experimental results of the proposed system surpassed the conventional ERS which yielded a rise in accuracy rate from 3.7% to 9.0%. The fusion of LPC and formants named as SFF LPC-fmnt indicated a promising result between 1.3% and 5.1% higher accuracy rate than its baseline features in classifying between neutral, angry, happy and sad emotions. The best accuracy rates yielded for male and female speakers were 79.1% and 79.9% respectively using SFF MFCC-fmnt fusion technique.
Co-Authors Alhan Farhanah Abd Rahim Emilia Noorsal Nor Fadzilah Mokhtar Yusnita Mohd Ali Zuhaila Mat Yassin