Development of Text to Speech System for Yoruba Language

Text-to-speech (TTS) applications have been applied to different languages in diverse areas of human endeavour all over the world, but for Yoruba language which is being spoken by over 30 million people out of 150 million Nigerian populace and in other countries like Benin, Togo, United Kingdom and part of South American, much has not been achieved therefore, there is need to develop TTS system for Yoruba language. This paper gives an account of Yoruba TTS system development using concatenation method. The paper describes the design, evaluation and the analysis of the result shows that 70% Respondents accepted its usability. Keywords: TTS, evaluation, concatenation, usability and design

Development of a Feature Extraction Technique for Online Character Recognition System

Character recognition has been a popular research area for many years because of its various application potentials. Some of its application areas are postal automation, bank cheque processing, automatic data entry, signature verification and so on. Nevertheless, recognition of handwritten characters is a problem that is currently gathering a lot of attention. It has become a difficult problem because of the high variability and ambiguity in the character shapes written by individuals. A lot of researchers have proposed many approaches to solve this complex problem but none has been able to solve the problem completely in all settings. Some of the problems encountered by researchers include selection of efficient feature extraction method, long network training time, long recognition time and low recognition accuracy. This paper developed a feature extraction technique for online character recognition system using hybrid of geometrical and statistical features. Thus, through the integration of geometrical and statistical features, insights were gained into new character properties, since these types of features were considered to be complementary. Keywords: Character recognition, Feature extraction, Geometrical Feature, Statistical Feature, Character

A comparative analysis of selected clustering algorithms for criminal profiling

Several criminal profiling systems have been developed to assist the Law Enforcement Agencies in solving crimes but the techniques employed in most of the systems lack the ability to cluster criminal based on their behavioral characteristics. This paper reviewed different clustering techniques used in criminal profiling and then selects one fuzzy clustering algorithm (Expectation Maximization) and two hard clustering algorithm (K-means and Hierarchical). The selected algorithms were then developed and tested on real life data to produce "profiles" of criminal activity and behavior of criminals. The algorithms were implemented using WEKA software package. The performance of the algorithms was evaluated using cluster accuracy and time complexity. The results show that Expectation Maximization algorithm gave a 90.5% clusters accuracy in 8.5s, while K-Means had 62.6% in 0.09s and Hierarchical with 51.9% in 0.11s. In conclusion, soft clustering algorithm performs better than hard clustering algorithm in analyzing criminal data. Keywords: Clustering Algorithm, Profiling, Crime, Membership valu

The Patterns of Acquisition of Syntactic Regularities in Pre-Secondary School Second Language Learners of English

The learning of complex syntactic structures of English by L2 learners have not been systematically dealt with in the available literature. This study investigated this problem, with the aim of replicating some works done in the L1, in order to determine their feasibility in the L2 perspective. Limited to a small sample, the study examined the developmental stages in the acquisition of English syntactic structures in 7 to 10-year-old children learning English as a second language. Six test constructs were used to examine linguistic competence over a wide range of surface structures, and statistical analysis provided the basis for interpretation of the general pattern of acquisition. The findings of the study show that the process of acquisition of syntactic structures continues actively during and after the primary school years among L2 learners, and they have implication not only for syntactic acquisition, but for language theory in general and L2 theory in particular

AN INTELLIGENT CLASSIFIER FUSION TECHNIQUE FOR IMPROVED MULTIMODAL BIOMETRIC AUTHENTICATION USING MODIFIED DEMPSTER-SHAFER RULE OF COMBINATION

Multimodal biometric technology relatively is a technology developed to overcome those limitations imposed by unimodalbiometric systems. The paradigm consolidates evidence from multiple biometric sources offering considerableimprovements in reliability with reasonably overall performance in many applications. Meanwhile, the issue of efficient andeffective information fusion of these evidences obtained from different sources remains an obvious concept that attractsresearch attention. In this research paper, we consider a classical classifier fusion technique, Dempster’s rule of combinationproposed in Dempster-Shafer Theory (DST) of evidence. DST provides useful computational scheme for integratingaccumulative evidences and possesses the potential to update the prior every time a new data is added in the database.However, it has some shortcomings. Dempster Shafer evidence combination has this inability to respond adequately to thefusion of different basic belief assignments (bbas) of evidences, even when the level of conflict between sources is low. Italso has this tendency of completely ignoring plausibility in the measure of its belief. To solve these problems, this paperpresents a modified Dempster’s rule of combination for multimodal biometric authentication which integrates hyperbolictangent (tanh) estimators to overcome the inadequate normalization steps done in the original Dempster’s rule ofcombination. We also adopt a multi-level decision threshold to its measure of belief to model the modified Dempster Shaferrule of combination.Keywords: Information fusion, Multimodal Biometric Authentication, Normalization technique, Tanh Estimators

Eco-conflict in Niyi Osundare’s Horses of Memory: An Interface between the Natural and the Built Environments

In our exploration of eco-conflict between the natural and the built environments, we examined Niyi Osundare‟s the “road crosses the river” metaphor in order to examine how the poems represent the social and aesthetic values of the natural and built environments. We analyze poems adopted from poem “XV” in “The Dream, the Dream is a Moon,” in Moonsongs; “Forest Echoes”, “The Rocks Rose to Meet Me” and “Harvestcall” in The Eye of the Earth. We adopt a contextual analysis approach of “Memory‟s Road” (II.90 -163) in Horses of Memory and subject same to content analyses. The study applies the eco-critical theory. Our findings show that man‟s handling of the environment is determined and limited to his knowledge of nature and his worldviews. However, there are those who are conscious of the danger of environmental degradation, but are constrained by economic, political and social considerations. While nature can do without human culture and structural beauty, the human society depends solely on the delicate balance of the eco-system for his survival. The social and aesthetic implications of eco-conflicts are thus succinctly constructed through the literary dynamics of eco-poetics

Eco-Conflict Management, Resolution and Prevention in Eco-Poetics: An Interface Between the Natural and The Built Environment

The interplay and the dynamics of human interest: ideology, idiosyncrasy, belief, ethnicity, social stratification, race and language are key factors in the promotion of human conflicts. Conflict management and resolution has often been human-focused while studies that concerns eco-conflict between the natural and the built environment are far between. This paper intends to explore eco-conflict management, resolution and prevention through selected nature-poems with specific reference to Niyi Osundare’s use of metaphor and imagery in “The Road crosses the River” and other related nature poems. The paper combines the eco-criticism theory, a critical approach which attempts to find a meeting point between literature and the environment and the theory of conflict management which contends that conflict is a state of incompatibility among values. We deduced from our findings that man has largely defrauded the natural environment through wanton exploitation, domestication of the natural environment and the consequent depletion of the eco-system in particular. The eco-conflict management, resolution, prevention, the dialectics of sustainability of the natural and the built environments are succinctly resolved through the literary dynamics of eco-poetic

Modeling and experimental investigation of lightning arcs and overvoltages for medium voltage distribution lines

In this dissertation, lightning overvoltages in Medium Voltage (MV) lines are thoroughly investigated. The other goal is to propose new protection schemes for the designs. The lines consist of overhead lines, underground cables and covered conductors. These overvoltage problems range from direct and indirect strokes to lightning arcs. All the models and simulations are developed using the Electromagnetic Transient Program (EMTP) and Finite Element Method (FEM), while MATLAB is used for post-processing the results and identification of the model parameters. Improvement in the surge protection of MV overhead lines is demonstrated with a combination of surge arresters and a shield wire. Using the IEEE 34-node feeder injected with multiple lightning strokes, the feeder is simulated using EMTP. The response of the line is modeled both with and without the surge protection devices. The simulation study extends to the performance of a MV underground cable due to a nearby lightning discharge using FEM. The use of shield wire for limiting the overvoltage stress in the cables is proposed. A numerical analysis and simulations are performed to determine the outage rate of MV covered conductors due to lightning strokes of different characteristics. The optimum distance for surge protective devices on the conductors is also assessed. An enhancement in the surge analysis of distribution lines with the shielding effect of trees is proposed. An experimental study shows that a tree can intercept a lightning stroke in the vicinity of a distribution line. This study also analyzes experimental results of the shielding effectiveness of a tree and the induced voltages existing between the tree and the distribution line. The study is extended to evaluate the induced voltage on a distribution line for larger clearances using a Rusck model. This work investigates the lightning arc between an overhead line and a nearby tree under artificial rainfall. A full-scale laboratory experiment confirms that a direct stroke to a tree can cause severe damage to nearby power lines by initiating an arc channel through air to the conductors. A complete model of this phenomenon is developed by combining the existing static and dynamic arc equations. The model is accomplished by the bilateral interaction between the EMTP and Transient Analysis Control System (TACS) field. The experimental results have been reproduced by the computer simulations. The performance of the arc phenomenon is examined using a typical Finnish distribution network design. Using the modified arc model, the lightning arc performance of the MV/ LV network under the influence of nearby trees and the network characteristics is evaluated

Comparison of Machine Learning Classifiers for Recognition of Online and Offline Handwritten Digits*

Automated recognition of handwritten digits has applications in several industries such as Postal and Banking for reading of addressed packages and cheques respectively. This paper compares four machine learning classifiers namely Naive Bayes, Instance Based Learner, Decision Tree and Neural Network for single digit recognition. Our experiments were conducted using the WEKA machine learning tool on two datasets; the MNIST offline handwritten digits and a collection of online ISGL handwritten digits acquired with a pen digitiser. Experiments were designed to allow for comparison within the datasets in a cross validation and across them where the online dataset is used for training and the offline dataset for testing and vice versa. We also compared classification accuracy at different levels of down sampling. Results indicate that the lazy learning instance based classifier performed slightly better than the neural network with a maximal accuracy of 97.86% and they both outperformed the other two classifiers: Naive Bayes and Decision Tree. The decision tree gave the worst performance of the four classifiers. We also discovered that better results were obtained with using the online digits when tested in a cross validation experiment. However, the pre-processed MNIST offline digits gave higher accuracies when used for training and tested with the online ISGL digits not vice versa. Also, we discovered down sampled size of 14x14 gave the best results for most of the four classifiers although these were not significantly different from the other down sampled sizes of 7x7, 21x21 and 28x28. We intend to investigate the performance of these classifiers in recognition of other characters (alphabets, punctuation and other symbols) as well as extend the recognition task to other levels of text granularity such as words, sentences and paragraphs. Keywords: Digits recognition, machine learning, classifiers, handwritten character recognition, Wek