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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Indonesian Journal of Electrical Engineering and Computer Science
Teddy Surya Gunawan
ECE Department Faculty of Engineering 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.
Design of Automatic Number Plate Recognition on Android Smartphone Platform Teddy Surya Gunawan; Abdul Mutholib; Mira Kartiwi
Indonesian Journal of Electrical Engineering and Computer Science Vol 5, No 1: January 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v5.i1.pp99-108

Abstract

Automatic Number Plate Recognition (ANPR) is an intelligent system which has the capability to recognize the character on vehicle number plate. It is a combination of hardware and software designed to offer the optimum reliability. Since the past decades, many researchers have been proposed to recognize the vehicle number plate and implemented it in various access control, law enforcement and security, including parking management system, toll gate access, border access, tracking of stolen vehicles and traffic violations (speed trap, illegal parking, etc). However, previous researches implemented ANPR system on personal computer (PC) with high resolution camera and high computational capability. On the other hand, not many researches have been conducted on the design of ANPR in Android smartphone platform which has limited camera resolution and limited computational power. The main challenges of implementation ANPR algorithm on smartphone are higher coding efficiency, lower computational complexity, and higher the scalability. The objectives of this research is to design ANPR on Android smartphone, including graphical user interface (GUI) design, process design, and database design. First, a comprehensive survey on the pre-processing, segmentation, and optical character recognition is conducted. Secondly, proposed system development and algorithm implementation is explained in more details. Results show that our proposed design can be implemented effectively in Android smartphone platform.
Development of Educational Game for Primary School Mathematics using Microsoft Kinect Teddy Surya Gunawan; Bakhtiar Bahari; 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.pp457-463

Abstract

This research focuses on the design and development educational game using Microsoft Kinect. The edugame can be used as educational tool in a classroom as to create an interesting and interactive learning process. This research is also focused on mathematics as its educational content using Microsoft Visual C#, XNA Game Studio, Microsoft Kinect for Windows SDK, and Microsoft Kinect as the main hardware. There are about eleven topics regarding mathematics based on the module provided by the Malaysian Ministry of Education. The interface of the game has been designed and developed to be interactive and attractive using some cartoon graphics, such as Ipin, Boboiboy, and Yaya. The developed game is a quiz base program, where student will have 10 questions each round and 4 choices of answers for every question. Currently, this educational game is designed for Year 1, Year 2 and Year 3 primary school students, and it has been evaluated by a group of 8 students. Furthemore, it has been evaluated and validated by a school teacher, in which they confirm the effectiveness of the developed game to improve student’s learning on Mathematics.
Development of Javanese Speech Emotion Database (Java-SED) Fatchul Arifin; Ardy Seto Priambodo; Aris Nasuha; Anggun Winursito; Teddy Surya Gunawan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3888

Abstract

Javanese is one of the most widely spoken regional languages in Indonesia, alongside other regional languages. Emotions can be recognized in a variety of ways, including facial expression, behavior, and speech. The recognition of emotions through speech is a straightforward process, but the outcomes are quite significant. Currently, there is no database for identifying emotions in Javanese speech. This paper aims to describe the creation of a Javanese emotional speech database. Actors from the Kamasetra UNY community who are accustomed to performing in dramatic roles participated in the recording. The location where recordings are made is free of interference and noise. The actors of Kamasetra have simulated six types of emotions, including happy, sad, fear, angry, neutral, and surprised. The cast consists of ten people between the ages of 20 and 30, including five men and five women. Both humans (30 Javanese-speaking verifiers ranging in age from 17 to 50) and a machine learning system (30 Javanese-speaking verifiers with ages between 17 and 50) verify the database that has been created. The verification results indicate that the database can be used for Javanese emotion recognition. The developed database is offered as open-source and is freely available to the research community at this link https://beais-uny.id/dataset/
Co-Authors Abdul Mutholib Anggun Winursito Anis Nurashikin Nordin Ardy Seto Priambodo Aris Nasuha Bakhtiar Bahari Fatchul Arifin Fathiah Abdul Muin Hasmah Mansor Intan Rahmithul Husna Yaldi Iza Zayana Yaacob Malik Arman Morshidi Mira Kartiwi Mira Kartiwi Mira Kartiwi Muhammad Fahreza Alghifari Muhammad Khalif Mat Zain Nanang Ismail Nor Farahidah Za'bah Siti Amalina Mohammad Hanafiah