Evaluates the Prognosis Of AI-Powered Voice-Guided System Aided for Individuals with Partial Disabilities Using Machine Learning.
Keywords:
CNN, RNN, IVR, TTS, voice control, home automation, self-assistance, and disabled individualsAbstract
Design of a new low-cost self-assistance system that facilitates the operation of household appliances and wheelchairs by using sophisticated voice commands from individuals with disabilities. With the modern advancements in technologies, each individual nowadays is moving over to an easier and more effective lifestyle. People are moving on with technology and finding solutions to problems faced in everyday life. Normal people are getting privileges of technology but sometimes the benefits could not reach the partially disabled ones. Partially disabled face a number of problems in day-to-day lives from navigation to communicating with others. The partially sighted people and hearing-impaired ones try to cope up with the normal ones but they do not get many opportunities. The study focuses on partially disabled people to provide them with some of the features to overcome few of the problems faced in the real world. This project demonstrates the aid for the partially visual and hearing impaired through communication via voice for the visually impaired and communication via text for the hearing impaired. The project is divided into two parts, initially consisting of text-to-speech and voice-to-speech capabilities, and object recognition for people with disabilities. This project includes a brief analysis of various models and algorithms such as interactive speech response (IVR), convolutional neural network (CNN), recurrent neural network (RNN), and Text-to-speech (TTS). Another part is the integration with Android applications. Here, the trained deep learning model serves as the source for the backend in object detection. Models are imported to predict outcomes, and text-to-speech helps people with disabilities access a variety of features such as voice-based email, object recognition, and virtual navigation.
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