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All Journal International Journal of Electrical and Computer Engineering JOIV : International Journal on Informatics Visualization Emerging Science Journal
Ong, Lee-Yeng
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Computer Science & IT Electrical & Electronics Engineering Environmental Science

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Journal : Emerging Science Journal

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SlowFast-TCN: A Deep Learning Approach for Visual Speech Recognition Ha, Nicole Yah Yie; Ong, Lee-Yeng; Leow, Meng-Chew
Emerging Science Journal Vol 8, No 6 (2024): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-06-024

Abstract

Visual Speech Recognition (VSR), commonly referred to as automated lip-reading, is an emerging technology that interprets speech by visually analyzing lip movements. A challenge in VSR where visually distinct words produce similar lip movements is known as homopheme problem. Visemes are the basic visual units of speech that are produced by the lip movements and positions. Furthermore, visemes are typically having shorter durations than words. Consequently, there is less temporal information for distinguishing between different viseme classes, leading to increased visual ambiguity during classification. To address this challenge, viseme classification must not only extract lip image spatial features, but also to handle visemes of varying durations and temporal features. Therefore, this study proposed a new deep learning approach SlowFast-TCN. SlowFast network is used as the frontend architecture to extract the spatio-temporal features of the slow and fast pathways. Temporal Convolutional Network (TCN) is used as the backend architecture to learn the features from the frontend to perform the classification. A comparative ablation analysis to dissect each component of the proposed SlowFast-TCN is performed to evaluate the impact of each component. This study utilizes a benchmark dataset, Lip Reading in Wild (LRW), that focuses on English language. Two subsets of the LRW dataset, comprising of homopheme words and unique words, represent the homophemic and non-homophemic dataset, respectively. The proposed approach is evaluated on varying lighting conditions to assess its performance in real-world scenarios. It was found that illumination can significantly affect the visual data. Key performance metrics, such as accuracy and loss are used to evaluate the effectiveness of the proposed approach. The proposed approach outperforms traditional baseline models in accuracy while maintaining competitive execution time. Its dual-pathway architecture effectively captures both long-term dependencies and short-term motions, leading to better performance in both homophemic and non-homophemic datasets. However, it is less robust when dealing with non-ideal lighting scenarios, indicating the need for further enhancements to handle diverse lighting scenarios. Doi: 10.28991/ESJ-2024-08-06-024 Full Text: PDF
From Teaching to Employability: The Cultural and Performance Pathways to Success Almaqbali, Said; Meng-Chew , Leow; Shannaq , Boumedyen; Marhoubi, Asmaa H.; Ong, Lee-Yeng
Emerging Science Journal Vol. 9 No. 5 (2025): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-05-027

Abstract

The current research examines the possible mediating and moderating effects of Teaching Efficacy (TE) and National Culture (NC) on the nexus of Readiness of Students (RS), Interactive Online Collaboration (IOC), Faculty Training (FT), and Policy Support (PS) and the ensuing results of Student Performance (SP), Job Employment (JE), Student Competency (SC), and University Reputation (UR). We have evaluated both the direct and indirect association between the stipulated constructs by utilizing Partial Least Squares Structural Equation Modeling (PLS -SEM) on a sample of 291 respondents who were sampled using structured questionnaires. The empirical evidence suggests that TE is a medium of connecting between RS, PS, and SP and therefore enhances its impact on JE, SC, and UR. Notably, the influence of SP on JE is statistically significant in case of concurrent TE activity (O for indirect path = 0.215, p<0.001). Similarly, mediation helped students score better on SC (O = 0.327, t = 6.261, p < 0.001) and UR (O = -0.065, t = 1.911, p = 0.028). A substantial direct correlation was found between RS and TE (r = 0.282, t = 4.175, p < 0.001). The outcome of the moderate analysis indicated that Organizational Culture exerted a strong influence, leading to a positive impact on the correlation between TE and SP (O = 0.087, t = 1.994, p = 0.023). In addition, Information Culture (IC) acted as a protective factor, moderating the relationship between RS and TE (O = -0.093, t = 1.945, p = 0.026). Taking TE as the main factor and cultural elements as moderators significantly improved the model's performance, demonstrating that student results and university reputation can be enhanced when there is strong teaching competence and a positive organizational environment within these institutions.
Co-Authors AlMaqbali, Said Goo, Cui-Ling Ha, Nicole Yah Yie Kai, Tan Juan Leow, Meng-Chew Marhoubi, Asmaa H. Meng-Chew , Leow Shannaq , Boumedyen