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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Indonesian Journal of Electrical Engineering and Computer Science
Mira Kartiwi
IS Department Faculty of ICT International Islamic University Malaysia
Computer Science & IT Electrical & Electronics Engineering

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A Review on Emotion Recognition Algorithms using Speech Analysis Teddy Surya Gunawan; Muhammad Fahreza Alghifari; Malik Arman Morshidi; Mira Kartiwi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 1: March 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i1.409

Abstract

In recent years, there is a growing interest in speech emotion recognition (SER) by analyzing input speech. SER can be considered as simply pattern recognition task which includes features extraction, classifier, and speech emotion database. The objective of this paper is to provide a comprehensive review on various literature available on SER. Several audio features are available, including linear predictive coding coefficients (LPCC), Mel-frequency cepstral coefficients (MFCC), and Teager energy based features. While for classifier, many algorithms are available including hidden Markov model (HMM), Gaussian mixture model (GMM), vector quantization (VQ), artificial neural networks (ANN), and deep neural networks (DNN). In this paper, we also reviewed various speech emotion database. Finally, recent related works on SER using DNN will be discussed.
Artificial Neural Network Based Fast Edge Detection Algorithm for MRI Medical Images Teddy Surya Gunawan; Iza Zayana Yaacob; Mira Kartiwi; Nanang Ismail; Nor Farahidah Za'bah; Hasmah Mansor
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp123-130

Abstract

Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes or discontinuities occur. Many traditional algorithms have been proposed to detect the edge, such as Canny, Sobel, Prewitt, Roberts, Zerocross, and Laplacian of Gaussian (LoG). Moreover, many researches have shown the potential of using Artificial Neural Network (ANN) for edge detection. Although many algorithms have been conducted on edge detection for medical images, however higher computational cost and subjective image quality could be further improved. Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. First, we developed features based on horizontal, vertical, and diagonal difference. Then, Canny edge detector will be used as the training output. Finally, optimized parameters will be obtained, including number of hidden layers and output threshold. Results showed that the proposed algorithm provided better image quality while it has faster processing time around three times time compared to other traditional algorithms, such as Sobel and Canny edge detector.
Investigation of Lossless Audio Compression using IEEE 1857.2 Advanced Audio Coding Teddy Surya Gunawan; Muhammad Khalif Mat Zain; Fathiah Abdul Muin; Mira Kartiwi
Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 2: May 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v6.i2.pp422-430

Abstract

Audio compression is a method of reducing the space demand and aid transmission of the source file which then can be categorized by lossy and lossless compression. Lossless audio compression was considered to be a luxury previously due to the limited storage space. However, as storage technology progresses, lossless audio files can be seen as the only plausible choice for those seeking the ultimate audio quality experience. There are a lot of commonly used lossless codecs are FLAC, Wavpack, ALAC, Monkey Audio, True Audio, etc. The IEEE Standard for Advanced Audio Coding (IEEE 1857.2) is a new standard approved by IEEE in 2013 that covers both lossy and lossless audio compression tools. A lot of research has been done on this standard, but this paper will focus more on whether the IEEE 1857.2 lossless audio codec to be a viable alternative to other existing codecs in its current state. Therefore, the objective of this paper is to investigate the codec’s operation as initial measurements performed by researchers show that the lossless compression performance of the IEEE compressor is better than any traditional encoders, while the encoding speed is slower which can be further optimized.
Development of Photo Forensics Algorithm by Detecting Photoshop Manipulation using Error Level Analysis Teddy Surya Gunawan; Siti Amalina Mohammad Hanafiah; Mira Kartiwi; Nanang Ismail; Nor Farahidah Za'bah; Anis Nurashikin Nordin
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp131-137

Abstract

Nowadays, image manipulation is common due to the availability of image processing software, such as Adobe Photoshop or GIMP. The original image captured by digital camera or smartphone normally is saved in the JPEG format due to its popularity. JPEG algorithm works on image grids, compressed independently, having size of 8x8 pixels. For unmodified image, all 8x8 grids should have a similar error level. For resaving operation, each block should degrade at approximately the same rate due to the introduction of similar amount of errors across the entire image. For modified image, the altered blocks should have higher error potential compred to the remaining part of the image. The objective of this paper is to develop a photo forensics algorithm which can detect any photo manipulation. The error level analysis (ELA) was further enhanced using vertical and horizontal histograms of ELA image to pinpoint the exact location of modification. Results showed that our proposed algorithm could identify successfully the modified image as well as showing the exact location of modifications.
Prototype Design of Smart Home System using Internet of Things Teddy Surya Gunawan; Intan Rahmithul Husna Yaldi; Mira Kartiwi; Nanang Ismail; Nor Farahidah Za'bah; Hasmah Mansor; Anis Nurashikin Nordin
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp107-115

Abstract

Smart home control system can be integrated into an existing home appliances to reduce the need for human intervention, increase security and energy efficiency. However, it is still an open problem due to difficulties such as network distance, signal interference, not user friendly, increased cost and power consumption. This paper reviews various topics on smart home technologies including control system, smart home network, smart home appliance and sensor technologies for smart home. In this research, the proposed prototype of home automation allows users to remotely switch on or off any household appliance based on Internet of Things (IoT) with the enhancement of solar charger. The smartphone and/or tablet replaces the manual use of personal computer without the need for high additional cost. This prototype uses four types of sensors i.e. PIR sensor, temperature sensor, ultrasonic sensor and smoke gas sensor for automatic environmental control and intrusion detection.
Co-Authors Anis Nurashikin Nordin Fathiah Abdul Muin Hasmah Mansor Intan Rahmithul Husna Yaldi Iza Zayana Yaacob Malik Arman Morshidi Muhammad Fahreza Alghifari Muhammad Khalif Mat Zain Nanang Ismail Nor Farahidah Za'bah Siti Amalina Mohammad Hanafiah Teddy Surya Gunawan