VIDEO CONFERENCING WITH CC FOR IMPAIRED HEARING USING NLP

Computer Engineering

This paper proposes an innovative approach to address the communication challenges faced by individuals with impaired hearing during video conferencing. The purpose is to improve the accessibility and inclusivity of virtual communication platforms by integrating Natural Language Processing (NLP) techniques and Closed Captioning (CC) functionalities. The proposed system employs advanced NLP algorithms to enhance real-time speech recognition and language understanding, catering specifically to the nuances of diverse accents, speech patterns, and contextual cues. By leveraging these capabilities, the system aims to provide accurate and contextually relevant transcriptions of spoken content within the video conferencing environment. In addition to the NLP-driven transcription, the research focuses on the integration of dynamic Closed Captioning to generate synchronized, visually accessible text alongside the video feed. This feature ensures that participants with impaired hearing can follow the conversation more effectively, capturing not only spoken words but also non-verbal cues, enhancing the overall communication experience.

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