Cross-Language Question-Answering System Using Hugging-Face Transformers

This research paper describes a Cross-Language Question-Answering (CLQA) program in Python using the Flask framework that uses Hugging-Face transformers for Question-Answering and Translation operations. The system uses the NLP library for question-answering using a fine-tuned model and translation jobs across English, Russian, French, and Spanish. The study emphasises inclusivity and user-friendliness, allowing people to ask questions in their chosen language and receive responses in their preferred language. The translation tasks are evaluated using conventional metrics. The findings highlight the CLQA system’s accuracy in generating replies, indicating its potential to improve accessibility and usability across varied language situations.