Abstract:
The language barrier between English and Japanese speakers presents a persistent challenge for tourists, students, and professionals visiting Japan. While popular translation tools such as Google Translate and Microsoft Translator provide general-purpose translations, they frequently fail to capture contextual nuances, idiomatic expressions, and cultural meanings, resulting in inaccurate or misleading interpretations. This project aims to develop an English-Japanese translation application utilizing Natural Language Processing (NLP) techniques to deliver context-aware, culturally sensitive, and accurate translations tailored for students and travelers.
The proposed system integrates Optical Character Recognition (OCR) for text extraction, Natural Language Understanding (NLU) for contextual analysis, and Machine Translation (MT) based on deep learning models, including LSTM and Transformer architectures. These models are trained using bilingual corpora to enhance translation accuracy and semantic relevance. Additionally, the application incorporates features such as pronunciation assistance and cultural insights, improving usability and user experience.
Evaluation of the prototype demonstrates substantial improvements over existing tools, achieving an average accuracy rate of 89%, surpassing baseline systems by more than 20%. User testing with real-world samples such as menus, signs, and travel guides indicated higher satisfaction due to enhanced contextual translation and pronunciation support. The findings highlight the potential of NLP-driven translation systems in overcoming communication barriers and promoting cultural understanding. This research contributes to both computational linguistics and cross-cultural communication, providing a foundation for future work in real-time, multilingual translation systems.
