As per the universal principles of usability and sustainable development goal defined for reducing inequality, each individual will have special abilities and challenges. Individuals with visual challenges have trouble interacting with digital platforms. In order to achieve inclusivity, there is a need to integrate universal accessibility into the web portals which are used as the most popular digital platforms. This study mainly focuses on the requirements of visually impaired users. The research work discusses the proposed approach for a telemedicine web platform by integrating voice navigation system. With this system, users can orally interact with the platform by using defined commands. Users can also receive the audio feedback from the computer for the specific command. The proposed speech recognition engine is implemented using deep learning models and tested on various browsers. The engine captures the commands in the form of user inputs and generates the proper audio feedback after executing the commands. Users with visual impairment have been involved in the evaluation by allowing them to interact on the telemedicine platform with verbal commands. The evaluation questions have been asked after each interaction to capture the response time, accuracy, experience and satisfaction. The outcome of the evaluation shows that individuals are showing significant progress in accessing required information and navigating the web pages on their choice of browsers. The study also observed that speech recognition engine along with speech grammar, acoustic model and synthesis has improved the usage of the system for all types of users. Ultimately, integrating voice navigation into web platforms provides a satisfactory experience to the users and improves accessibility, inclusivity and reduces inequality.
