Reduced Database for Voice Commands Recognition Using Cloud Technologies, Artificial Intelligence and Deep Learning

Voice commands recognition tasks used limited sets of words in comparison of universal speech recognition systems dedicated to work with the whole set of words of one or more that one natural languages. Today these universal speech recognition systems are usually based on cloud technologies, artificial intelligence and probably on neural networks with deep learning. The main drawback of using these universal speech recognition systems in tasks like voice commands recognition is the need of unnecessary search the limited set of words (a few words of voice commands) in the databases, containing very large set of words of a chosen natural language. Therefore, the proposition as the goal of this article is to combine the advantages of universal speech recognition systems using cloud technologies, artificial intelligence and neural networks with deep learning in voice commands recognition tasks, but creating and using the reduced database as an appropriate subset of the large speech recognition database existing as cloud databases.