Shahriman Abu Bakar

Malaysian English accents identification using LPC and formant analysis

In Malaysia, most people speak several varieties of English known as Malaysian English (MalE) and there is no uniform version because of the existence of multi-ethnic population. It is a common scenario that Malaysians speak a particular local Malay, Chinese or Indian English accent. As most commercial speech recognizers have been developed using a standard English language, it is a challenging task for achieving highly efficient performance when other accented speech are presented to this system. Accent identification (AccID) can be one of the subsystem in speaker independent automatic speech recognition (SI-ASR) system so that deterioration issue in its performance can be tackled. In this paper, the most important speech features of three ethnic groups of MalE speakers are extracted using Linear Predictive Coding (LPC), formant and log energy feature vectors. In the subsequent stage, the accent identity of a speaker is predicted using K-Nearest Neighbors (KNN) classifier based on the extracted information. Prior, the preprocessing parameters and LPC order are investigated to properly extract the speech features. This study is conducted on a small set speech corpus developed as pilot study to determine the feasibility of automatic AccID of MalE speakers which has never been reported before. The experimental results indicate a highly promising recognition accuracy of 94.2% upon feature fusion sets of LPC, formants and log energy.

Risk factors of musculoskeletal disorders among oil palm fruit harvesters during early harvesting stage.

This cross-sectional study intends to investigate the associations of musculoskeletal disorders (MSDs) among foreign labourers on a socio-economic background, occupational exposure, social lifestyle, and postures adopted during harvesting tasks. A total of 446 male respondents (263 FFB cutters; 183 FFB collectors) were studied using an interview-assisted questionnaire. OWAS was used to determine the severity of awkward posture based on videos of harvesting tasks recorded for each respondent. Analysis found that increasingly educated respondents had higher risk of developing MSDs. Shorter daily work duration and longer resting duration appear to increase the risk of neck and shoulder disorders among harvesters, which may be attributable to organizational work design. Awkward posture was a particularly significant risk factor of MSDs among FFB collectors. Among the results of the study, occupational exposure, postures and certain socio-demographic backgrounds explained some, but not all, the risk factor of MSDs among harvesters. An in-depth investigation, preferably a longitudinal study investigating the dynamic of work activities and other risk factors, such as psychosocial risk factors, are recommended.

Phoneme-based or isolated-word modeling speech recognition system? An overview

In this paper speech theories and some methodological concerns about feature extraction and classification techniques widely used in speech recognition system are surveyed and discussed. The shortage of isolated word speech recognition is addressed as compared to its phoneme-based counterpart. This paper could be regarded as a very early stage towards methodology establishment in searching for better accuracy and less complexity system which has more generic properties. It is hoped that the system can classify speech regardless of the varieties across languages or accents. Speaker independency (SI) manner speech recognition system is required for this application and in fact, in many other potential applications as much as a telephonic network (large database consists of many different speakers) is a primary requirement. Isolated-word ASR for fixed vocabularies has been successfully implemented using HMM, ANN and SVM but suffers from lack of adaptability to other languages and increase in complexity as number of vocabularies increases. Conversely, phonemes, the smallest unit of human speech sounds are apparently more feasible to represent the basic building block for cross-language mapping. In fact, the phonetic transcription systems such as IPA and SAMPA are widely recognized and standardized for several languages in the world. This paper intends to investigate the phoneme-based potential as language independent phonetic units to overcome the lack of available training data so as to achieve a more generic speech recognizer.

Feature Extraction and Optimum Part Deposition Orientation for FDM

Support generation is an essential for Fused Deposition Modeling (FDM) process which is dependent on part deposition orientation. Various part deposition orientation result in formation of different support and non-support features. Present work focuses on extracting the support features containing Externally-Supported Features (ESF) which are able to determine the volume and number of support structure. The methodology proposed in this work uses these information as an input for Artificial Neural Network (ANN) in order to automate the selection of optimum part deposition orientation. The results produced in present methodology can be predicted and are in agreement with the results published earlier.

Investigation of Steering Wheel Control of an Electric Buggy Car for Designing Fuzzy Controller

Steering control for path tracking and navigation are important for the autonomous vehicle. A good steering control system can determine the success of autonomous navigation through designed paths. Comfort and safety for the passenger are the main concerns in developing a controller for an autonomous electric vehicle (AEV). Comfort and the safe autonomous system can be achieving by imitating human intelligence and decision-making ability into the controller. A GPS module couple with a fuzzy controller to follow the designed path. Steering is control by using brushless DC motor with certain gear configuration. In order to achieve better drive performance for the autonomous vehicle, the behaviors of human subjects are studied and investigated. Investigation of steering angle on 3 different paths is designed to study the driving patterns by the human subjects, which are straight, turn right and turn left. The results show satisfactory outcomes as the subject navigates through the designed path with the similar patterns. The average value of steering wheel angle for the straight, right and left path are 13°, −151°, and 237°, respectively. The maximum angle to turning to the left and right are 286° (subject #1) and −226° (subject #1). This paper consists of the construction of a Fuzzy logic controller to control steering wheel and experiments set-up to develop the Fuzzy controller for an autonomous vehicle.

Ontological Framework of Arm Gesture Information for the Human Upper Body

In the research of the human motion analysis, the characteristic movements of the human upper body are intensively investigated for many applications such as sign language recognition, robot control and gait analysis. The human upper body consists of many body parts such as both arms including fingers, facials and head movements. Previously, many researches proposed various sensors to record arm movements and the acquired data are used to train the computer understand the behavioral motion of arms movements by using various algorithmic approaches. However, the current challenge is to increase the knowledge level of the computational systems to recognize gestural information containing in arm movements. The objective of this paper is to construct and derive the arm movement’s model based on the conceptual of ontology. The gestural information is investigated from characteristic features of arm movements. The knowledge of the computational systems about gestural information is developed by describing the characteristic features of arm movements in the form of the ontological framework. The ontological framework is defined as a structure containing characteristic features placed in mathematical order and has the relationship among them. Based on the mathematical model as proposed in this paper, the ontology framework could be used to describe knowledge of the arm gesture and could recognize it with a higher accuracy.

Study of Eddy Current Density Distribution in a Contactless Breast Cancer Detection Mechanism Using Magnetic Induction Spectroscopy

Breast cancer is a throbbing disease that no longer needs an introduction. This is especially true among women due to their unique breast structure that naturally has more breast tissues compared to that of man’s. It is been forecasted that in 2015, a minimum of 60290 new cases of breast cancer will be reported. The goal of this study is to analytically evaluate the changes in the induced Eddy current densities as a function of di-electrical properties of the breast tissue with respect to tumor positioning as well as its size. This is achieved by running numerical simulations on the proposed mechanism of magnetic induction to detect tumors among healthy breast tissue via a 2D breast model configuration. The analytical results presented in this article, proved that the multi frequency magnetic induction principle is viable in detecting the breast lesions as small as 0.2 cm non-invasively through the distributions of the induced Eddy current density. While important pattern of the induced current were reflected when the tumors are located at the far ends of the breast diameter. The minimum results computational time with the proposed system is 10 s.

Thermoelectric as recovery and harvesting of waste heat from portable generator

Generation of waste heat was ineluctable especially during energy producing process. Waste heat falls into low temperature grade make it complicated to utilize. Thermoelectric generator (TEG) offers opportunity to harvest any temperature grade heat into useful electricity. This project is covered about recovery and utilizing waste heat from portable electric generator by using a TEG which placed at exhaust surface. Temperature difference at both surfaces of TEG was enhanced with supplying cold air from a wind blower. It is found that, even at low air speed, the TEG was successfully produced electricity with aid from DC-DC booster. Results shows possibility to harvest low temperature grade heat and still exist areas for continual improvement.

Study on bovine bone surface after atmospheric plasma treatment

This paper studies of the effect on surface characteristics of bone surface after plasma treatment. For that purpose, the experimental procedure is designed to develop atmospheric plasma jet device. The physical processes such as electron dynamics, electron field, ionization and dissociation in relation to atmospheric pressure plasma are stated. The plasma jet is ignited in a glass tube with helium gas flowing freely into the surrounding air. Some consideration to develop the plasma jet is made to get stable plasma. In addition, its focuses on the surface analysis for bone surface after being treated to plasma. A few samples of freeze dried bovine bone were radiated in plasma. Then, the surfaces of bone were characterized in the term of surface morphological changes by using Scanning Electron Microscopy (SEM) and the data were analyzed to observe it differences. From the results of SEM, we could confirm that the main phenomena such as the reactive etching has modified the surface morphology.