Bridging Language Gaps: an Offline Mobile Translation App for Filipino Dialects

Language barriers among Filipino dialects pose challenges in effective communication, emphasizing the need for an accessible and reliable translation tool. This study developed an offline mobile translation app to facilitate seamless Tagalog-Bicol translation without requiring an internet connection. The system was designed using the Agile Software Development Model, enabling iterative improvements based on user feedback. Implemented in Python, the application utilized a Rule-Based Natural Language Processing (NLP) approach and a linear search algorithm for dictionary-based translation retrieval. Key features included an offline translation engine, text-to-text input, interactive user feedback, and gamified learning elements to enhance user engagement. The system was evaluated through NLP-based methodologies, including human assessment by native speakers to measure translation quality, fluency, and contextual accuracy, as well as usability testing to assess ease of use, responsiveness, and overall user experience. The results indicated that the app provided accurate translations and a user-friendly interface. This study contributes to language accessibility and digital inclusion by offering a practical solution for Filipino dialect translation.