Speech Recognition for Light Control on Raspberry Pi Using Python Programming

Abstract

The Internet of Things has been substantially developed for disabled and elderly persons in various domains. Speech recognition is an extremely challenging technique for cost-effective human contact, communication, and control. Numerous experiments have been undertaken on voice recognition systems in order to provide a more complete explanation of language commands, particularly for non-native English speakers and languages with tone variations. This article outlines the development of a Raspberry Pi-based spoken command system. The system was developed and installed using Python, and it makes use of the Google Speech Recognition API as a speech-to-text converter. Our light control system's speech recognition system is capable of receiving voice commands via a USB microphone. The experimental results compare the accuracy of light control for Thai and English orders utilizing individuals who are Thai elderly speakers. Thai speech is recognized more precisely than English speech by the suggested approach. These startling findings refute the concept that speech recognition algorithms can boost the growth of the Internet of Things. However, the system's accuracy in recognizing speech for disabled and elderly users should be weighed against the country's national or indigenous languages.