Audio to Sign Language Converter

Communication barriers between individuals with hearing impairments and those who do not understand sign language pose significant challenges in various social and professional settings. To address this issue, we propose an Audio-to-Sign Language Translation System that converts spoken language into corresponding sign language animations, improving accessibility and inclusivity. The system utilizes speech recognition, natural language processing (NLP), and sign language animation rendering to facilitate seamless translation. Speech input is captured via the Google Speech Recognition API, which converts audio into text. The text is then processed using NLP techniques such as tokenization, lemmatization, stop-word removal etc, to extract meaningful keywords. These keywords are mapped to a database of predefined sign language animations, ensuring accurate translation. If an exact match is unavailable, a character-wise animation approach is used to spell out the words. The system provides multiple input options, including realtime microphone input, text-based input, and audio file upload, enhancing its usability in diverse scenarios. The application interface allows users to interact with the translation process dynamically, ensuring a user-friendly experience.