Teknik-teknik mengenalpasti sela masa senyap dalam sistem pengecaman suara

Classification of speech into voiced, unvoiced and silence (V/UV/S) regions is an important process in many speech processing applications such as speech synthesis, segmentation and speech recognition system. Two such measures are investigated with respect to their ability to discern voiced/unvoiced and silence segments of speech. They are the Instantaneous Energy (IE) and Local Time Correlation (LTC) method. Both IE and LTC methods are recently proposed technique for nonstationary signal analysis and have been successfully applied to speech processing. A comparative study was made using these two algorithms for classifying a given speech segment into two classes: voiced/unvoiced speech and silence. IE and LTC methods were proposed to remove all the silent intervals in speech sample. Experiment are carried out using Linear Predictive Coding (LPC) and Dynamic Time Warping (DTW) for isolated digit recognition in Bahasa Malaysia. The technique without silent removal LPC-DTW gives a recognition accuracy of 98.28%. With detection and removing of silent interval, both technique IE-LPCDTW and LTC-LPC-DTW gives a recognition accuracy of 98%. The system then are applied for training and testing for connected digit recognition. The segmentation of input string of the digits are carried out using IE and LTC techniques. Connected digit recognition using IE-LPC-DTW had 93.3% digit accuracy and 78% digit string. However using LTC-LPC-DTW the performance decreased to 93.2% and 77.7% respectively

The Development Of System For Algorithms Visualization Using Simjava

Algorithm visualization which is a form of high-level dynamic visualization of software that uses user interface techniques to portray and monitor the computational steps of algorithms. Moreover, algorithm visualization systems are also useful tools in algorithm engineering, particularly at several stages during the design, implementation, analysis, tuning, experimental evaluation, and presentation of the algorithms process. Algorithms are a captivating use case for visualization. It does not simply fit data to a chart to visualize an algorithm, there is no main data set. Rather there are consistent principles that depict conduct. This is because algorithm visualizations are so uncommon, as designer's experiment with novel forms to better communicate. Algorithm visualization (AV) uses graphics to portray an algorithm's actions. AV holds the promise of helping computer science students understand algorithms more effectively and in more prominent profundity. The purpose of this study is to design a system for sorting algorithm visualization and implement the system

Cloud-To-Ground Lightning Flashes Under The Influence Of Pollution In Malaysia And Some Countries

The effect of air pollution produced from world war, industrial activities and transportation clearly can change the earth ecology system such as the atmospheric conditions. Base on few studies reported from by researcher in USA, Brazil, Spain and South Korea researcher have proven that the pollution effect can enhance the activity of lightning. Those information above motivate Advanced Multidisciplinary System Technology researcher in UTeM to report the cloud-to-ground lightning flashes in Malaysia the influence of pollution. Particulate Matter (PM10) and Sulfur Dioxide (SO2) concentration were used as gross indicator of Cloud Condensation Nuclei (CCN) and examined in relation to the urban increase in CG lightning activity. PM10 concentration recorded in Subang, Ipoh and Bayan Lepas were 51, 50 and 49μgm/m³ respectively. Meanwhile, SO2 concentration recorded were 8, 7.9, 7.7μgm/m³. The three urban areas have average number of CG lightning flashes of 200, 197 and 184. An analysis related number of CG flashes against pollutants show positive correlation in Malaysia with reading of 0.94. This indicates PM10 and SO2 concentration have high influential factor in enhancement of CG lightning activity in Malaysia

Permeance Based Algorithm For Computation Of Flux Linkage Characteristics Of Non-Linear 6/4 Switched Reluctance Motor (SRM)

The concept of permeance is used in the analysis of flux linkage of 6/4 SRM. The aim of this paper is to develop an efficient algorithm exploiting the nonlinear feature of the 6/4 SRM using the aforementioned concept of permeance. The first step is to generate the relevant equations related to permeances of the 6/4 SRM under study. The 6/4 SRM’s magnetization curve is then derived from the summation of mmf drops at various blocks representing the motor. The air gap permeances are derived at various angles and 3-D leakage effects are taken into account. These permeances are used for the mmf drop computation. The algorithm is capable of efficiently computing mmf drop at every block to consequently yield a complete accurate nonlinear flux linkage feature of the 6/4 switched reluctance motor. In this way, the capability of the SRM to produce the expected four times the specific output torque due to operation in high saturation region compared to an equivalent induction motor as special the attribute of the SRM is demonstrated

Signal segmentation and its application in the feature extraction of speech

Speech is considered as a time-varying signal since the parameters of the signal such as the amplitude, frequency and phase varies in time. Segmenting a duration of captured speech into analysis frames of 20 msecs ensures the assumption of stationarity. If a captured speech segment representing a word that may last for 600 msec, then a total of 30 analysis frames are required to the word. Due to the possibility that adjacent frames are identical, then it would be of interest to combine these frames into a single long frame. The interval where adjacent frames have identical parameters is referred as the time-invariant interval (TII). It is of interest to determine these intervals and two methods presented are the instantaneous energy and frequency estimation (IEFE) and localized time correlation (LTC) function. A comparison is made in the accuracy in the TII estimate for a set of speech sample

Speaker recognition based on Hidden Markov Model

In this paper, a method for implementing speaker recognition system using the discrete Hidden Markov Model. This method uses a statistical approach in characterizing speech. The speech utterance is fit into a probabilistic framework, which consist of transition of states and discrete observable sequences. The system is then applied to recognition of isolated Bahasa Melayu digits, that is 'kosong', 'satu', 'dua', 'tiga', 'empat', 'lima', 'enam', 'tujuh', 'lapan', and ·sembilan'. Experiments were done to evaluate the system's perfomance on speaker recognition. which can be further divided into speaker identification and speaker verification. Speaker recognition, experiments were performed to evaluate the performance of the system with 30 speakers (22 impostors and 8 clients). The identification error was 2%, the false acceptance rate was 28% and the false rejection rate was 1%

Sub Microsecond Analysis Of Negative Cloud-To-Ground Lightning Flashes

This paper expounds a software development for the identification of lightning discharged in cloud-to-ground flashes.The study was to reduce a misleading detection of the electric field radiation of lightning discharged profile by considering the important parameters of sub microseconds structure of lightning`s first return stroke.The software built in MATLAB.The software development considered the important parameters of the first return strokes such as peak value,zero crossing, rising time and fast transition time.This study used a modelling technique for training and patterning 19 return strokes from electric radiation field generated by the negative cloud-ground lightning flashes recorded in Universiti Teknikal Malaysia Melaka.19 return strokes data were recorded by using Lecoy HDO4024 with 5 MS/s.The results showed the software recognized the lightning parameters such as peak value,zero crossing,rising time and fast transition time.In conclusion,the software had the potential to decreases the misleading detection of the electric field radiation generated by negative cloud-to-ground lightning flashes

Cost Effective Remote Monitoring For Mini Hybrid Automation System

The growth of the communication system has been progressing rapidly and it provides facility in data acquisition system which can be remotely monitored via internet which so called Internet of Thing (IoT). In this project, a mini hybrid automation system is built and aims to produce energy for home appliances distributor. Circuit of the solar charger adapters available in the market will be carried out and the controller is able to distribute energy to all applications in the home. Research and analysis on the charger, solar and electric generator available in the market need for modification of the circuit. This project also includes research in solar charger, generator and the means of modification of the circuit. A standby generator is a back-up electrical system that operates automatically. Within seconds of a utility outage an automatic transfer switch senses the power loss, commands the generator to start and then transfers the electrical load to the generator. The standby generator begins supplying power to the circuits. The system with cost-effective control system based on Arduino as a microcontroller and TP-Link MR3020 for wireless internet communication with open source OpenWrt embedded firmware and all the operations can be monitored through web interface

An Analysis Of Manual And Autoanalysis For Submicrosecond Parameters In The Typical First Lightning Return Stroke

The mechanism on how lightning detection system (LDS) operated never been exposed by manufacturer since it was confidential. This scenario motivated the authors to explore the issue above by using MATLAB to develop autoanalysis software based on the feature extraction. This extraction is intended for recognizing the parameters in the first return stroke, and compare the measurement between the autoanalysis software and the manual analysis. This paper is a modification based on a previous work regarding autoanalysis of zero-crossing time and initial peak of return stroke using features extraction programming technique. Further, the parameter on rising time of initial peak is added in this autoanalysis programming technique. Finally, the manual analysis using WaveStudio (LeCroy product) of those two lightning parameters is compared with autoanalysis software. This study found that the autoanalysis produce similar result with the manual analysis, hence proved the reliability of this software