Rule-based AI for Virtual Voice Assistants

Abstract

Virtual Voice Assistant (VVA) is a service-based application that can understand and execute voice commands, or act as an intermediary for the systems. With the development of deep connections between humans and artificial intelligence voice assistants (VA), the relationship between humans and machines has been enhanced. This study purposed the rule-based framework for the Virtual Voice Assistant (VVA) that captured the user’s voice and performed an SST operation on it to extract the text. Furthermore applied NLP operations to preprocess the raw data and pass it to the rule-based dictionary for the appropriate action. This system is especially for people with differently-abled (blind, and handicap) and performs their tasks on the system.