Abstract

This paper develops and evaluates a microphone-free GUI-based speech recognition system capable of high accurate speech-to-text conversion without the use of any device. It explores in further detail the interplay amongst user interface design, techniques for noise removal, and database management in terms of enhancing the usability and performance. Five hypotheses are tested: the influence of GUI design on user interaction, the efficiency of noise removal by cross-correlation, the accuracy of microphone-free recognition, the role of database management in system scalability, and the comparative efficiency of the proposed system against existing technologies. A quantitative methodology is used with controlled experiments to analyze data from diverse users and environments. The results show that the GUI needs to be intuitive; cross-correlation is the efficient method for noise cancellation; and it is quite feasible to achieve recognition accuracies comparable to that using a microphone. Good management of the database ensures greater scalability and real-time processing. Finally, the system has an accuracy and efficiency compared with the existing technology in the field, thus providing great advancements in speech recognition. The study also considers limitations in environmental diversity and data availability, proposing further research into improving noise removal techniques and database strategies for broader applicability.