Handwriting recognition for Vietnamese script applied to digitalization of administrative records in Vietnam | |
| Author | Nguyen Dang Nguyen |
| Call Number | AIT Project no.PMDS-23-08 |
| Subject(s) | Optical character recognition Vietnamese language--Writing--Data Processing Writing--Data processing |
| Note | A project study submitted in partial fulfillment of the requirements for the degree of Professional Master in Data Science and Artificial Intelligence Applications |
| Publisher | Asian Institute of Technology |
| Abstract | Handwriting recognition technology plays a pivotal role in the digitalization of administrative records, a task of paramount importance in the modernization of governmental processes. This thesis delves into the development and implementation of handwriting recognition systems tailored specifically for the Vietnamese script. The unique characteristics and complexities of the Vietnamese script, with its diacritics and complex ligatures, pose significant challenges for automated recognition systems. The primary objective of this research is to design and evaluate a robust and accurate handwriting recognition system for Vietnamese administrative records. To achieve this, we conducted an in-depth analysis of the Vietnamese script's linguistic features, cultural context, and historical evolution. This analysis informed the development of a tailored recognition algorithm that effectively addresses the script's intricacies. Through a comprehensive evaluation process, utilizing a diverse dataset of handwritten administrative documents, we assessed the system's performance in terms of accuracy, efficiency, and scalability. My results demonstrate the effectiveness of the proposed recognition system in accurately transcribing handwritten Vietnamese text into digital format, thereby expediting the digitalization of administrative records. This research contributes to the broader field of handwriting recognition and holds significant implications for the efficient management of administrative records in Vietnamese governmental institutions. The successful implementation of such a system promises to streamline administrative processes, improve accessibility to historical records, and enhance overall efficiency in the public sector. Furthermore, I will conduct a small-scale experiment to compare and evaluate the performance of Apple's new integrated graphics processing unit (Apple Silicon M series) in executing machine learning training tasks, analysis, and image recognition. This aims to assess whether they are competitive enough with dedicated graphics cards. If they indeed prove to be effective, it may be suggested to apply them in hardware-equipped tasks to optimize the investment costs and management for VNPT's AI product development. This is because integrated chips tend to require less space and energy, offering potential advantages in these aspects. |
| Year | 2023 |
| Type | Project |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Professional Master in Data Science and Artificial Intelligence Applications (PMDS) |
| Chairperson(s) | Cherdsak Kingkan (Co-Chairperson);Chutiporn Anutariya (Co-Chairperson) |
| Examination Committee(s) | Vatcharaporn Esichaikul;Chantri Polprasert |
| Scholarship Donor(s) | AIT Scholarships |
| Degree | Professional Master in Data Science and Artificial Intelligence Applications - Asian Institute of Technology, 2023 |