Browsing by Author "Taiwo Mauyon KUPONU"

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    Leadership Styles, Motivation and Quality of Work Life as Determinants of Organisational Citizenship Behaviour among Lecturers in Private Universities in Southwest, Nigeria
    (Lead City University, 2023-12) Taiwo Mauyon KUPONU
    The observed issues of sabotage, floating and ready-to-leave attitude among some academic staff in private universities may be detrimental to a university’s interests. There is scarcity of empirical researches investigating influence of leadership styles, motivation and quality of work life on organisational citizenship behaviour of lecturers in private universities. This study investigated leadership styles, motivation and quality of work life as determinants of organisational citizenship behaviour among lecturers of private universities in Southwest, Nigeria. The study adopted the descriptive survey research design. One thousand, one hundred and fourty four lecturers in private universities in Southwest, Nigeria were selected using the multistage sampling procedure. Data were generated with a questionnaire on Leadership Styles, Motivation, Quality of Work Life and Organisational Citizenship Behaviour (α =.831). Data were analysed using descriptive and inferential statistics at 0.05 alpha level. The result showed that: there is a significant joint influence of leadership styles, motivation and quality of work life on organisational citizenship behaviour among lecturers of private universities in Southwest, Nigeria (R2=.931, F (3,1140) =5129.764); there is a significant relative influence of leadership styles (β =0.312; t=6.186), motivation (β= 1.111; t=15.739) and quality of work life (β= 0.492; t=28.278) on organisational citizenship behaviour of lecturers in private universities in Southwest, Nigeria; there is a significant positive relationship between quality of work life and organisational citizenship behaviour (r=0.785) among lecturers of private universities in Southwest, Nigeria; there is a significant moderating role of gender in the influence of quality of work life on organisational citizenship behaviour (Male, β =-.855; t=-39.297 and Female, β =.914; t=53.848) among lecturers of private universities in Southwest, Nigeria. Quality of work life should be enhanced among lecturers in private universities to ensure organisational citizenship behaviour, among other recommendations. Keywords: Leadership Styles, Motivation, Quality of Work Life, Organisational Citizenship Behaviour, Lecturers, Word Count: 288
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    Speech Recognition Algorithm of Major Nigerian Languages (Yoruba, Hausa, Ibo) Using K-NN
    (Lead City University, 2023-12) Taiwo Mauyon KUPONU
    This study addresses the crucial need for enhanced voice recognition systems in the realm of human-machine interfaces, particularly with a focus on accent identification algorithms, and their application in the context of Nigerian English speakers. The research aims to improve the accuracy and efficiency of speech recognition for these major Nigerian languages using KNN to increase the efficiency and accuracy of accent identification by using a trained data with the three major Nigerian language. Voiced audio samples of speakers from these tribes speaking English and various platforms such as news media and radio recordings was scrapped and recorded and extracted. The audio data was then preprocessed and transformed from the time domain to the frequency domain using the Fourier transform. Matlab R2015A was employed for model training, encompassing input reading, window size and hop size definition, and noise reduction techniques such as high-pass filtering and spectral subtraction. For feature extraction, Mel Frequency Cepstral Coefficients (MFCC) were computed for each audio frame, subsequently aggregated to create fixed-length representations for each dialect sample for about sixty seconds in order to ensure uniformity in the inputs. The model underwent training with a classification algorithm KNN, followed by evaluation, which gave an accuracy rate of 84%. This result indicates that the model proficiently predicts the dialects within the context of English speech. The study's outcomes signify substantial progress in the development of an accent detection model tailored to the major Nigerian tribes: Yoruba, Hausa, and Igbo. The research is a significant stride toward more precise and effective voice recognition systems for Nigerian English speakers, contributing to the broader advancement of human-machine interfaces in an increasingly technology-driven world. It is recommended that future research explores alternative feature extraction techniques, particularly deep learning-based approaches capable of automatically learning relevant features from raw audio data. Keywords: Accent. Accuracy, Algorithm, Dialect detection, Feature extraction, Fourier transform, Performance, Speech recognition, Voice recognition Word Count: 298 Words