Enhancing Patient Care Through NLP-Based Realtime Bidirectional Voice Translation in Healthcare

In healthcare settings, the language barrier between patients and medical professionals poses a significant challenge, impacting the quality of care and patient outcomes. Patients that struggle with language barriers to properly connect with their healthcare providers may face obstacles in receiving timely and accurate treatment. The proposed solution leverages bidirectional voice translation capabilities to facilitate communication between individuals who do not share a common language. This research introduces bidirectional voice translation technology as a solution to the language barrier in healthcare. Through the application of Natural Language Processing (NLP) and Speech Recognition algorithms, this mobile application enables real-time translation of spoken input between patients and medical professionals. By employing a mobile application accessible to both medical professionals and patients, this technology enables seamless communication in diverse linguistic settings. This innovation enhances communication, enabling accurate diagnosis, treatment, and explanation of medical procedures across diverse linguistic backgrounds. With multilingual support, sentiment analysis, and offline capabilities, this technology offers a promising avenue to improve patient care, health outcomes, and inclusivity in healthcare delivery.