Abstract
The bidirectional audio to sign language translation app presented in this paper aims to improve communication between spoken language users and the sign language community. Leveraging natural language processing (NLP) techniques, including syntactic analysis and lemmatization, the app provides real-time translation services with enhanced accuracy and naturalness. Developed using Flask for web application development, NLTK for NLP tasks, and the Stanford Parser for syntactic parsing, the system offers an intuitive interface for seamless translation between spoken language and sign language. Evaluation of the app demonstrates notable improvements in translation quality and user satisfaction, indicating its potential for widespread adoption and positive impact on communication accessibility and inclusivity. Index Terms -Bidirectional Audio, Sign Language Translation, Natural Language Processing (NLP), Flask Framework, NLTK Library, Stanford Parser.
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