Evaluation of the impact in reducing the number of parameters for continuous speech recognition for Brazilian Portuguese

With the advent of technology, machines predominate in almost all scenarios of everyday life. The possibility of performing human-machine communication through speech makes this interaction easier and more productive. However, processing requirements still make difficult the implementation of systems for automatic speech recognition on devices with low computational power such as mobile phones, palmtops and appliances. For this purpose, it becomes necessary to research for optimized acoustic and language modeling, associated with use of representative databases, looking for a good compromise between recognition rates and computational demands imposed by embedded systems. The main goal of this work is to model the architecture of a system for continuous speech recognition to Brazilian Portuguese, in order to enable its implementation in an embedded system with limited computing resources.