Research on Internet of Things Human-Computer Interaction System Based on Computer Artificial Intelligence Technology

This piece delves into the realm of the Internet of Things and explores the synergy between AI technology and human-machine interaction systems. Specifically, an analysis is conducted on the core of computer AI-driven dialogue processes and associated technologies, such as automated question answering, continuous speech recognition, and text-to-speech systems. Research indicates that AI technology greatly enhances the efficiency and accuracy of these interaction systems, particularly in handling continuous streams of natural language input and output. A deeper analysis of the automated question answering system reveals its reliance on sophisticated natural language processing and knowledge graph technologies, aiming to enhance the quality of problem analysis and response generation. Similarly, the exploration of continuous speech recognition systems demonstrates their pivotal role in converting speech information into text accurately, which is vital for achieving smooth human-machine conversations. Furthermore, the analysis of text-to-speech systems highlights the natural and fluid transformation of textual information into speech output through advanced speech synthesis technology. To ensure practicality and the actual effectiveness of the design, a series of system validation tests are proposed and implemented in this study. These tests evaluate the core performance indicators of the system, with recognition rate tests focusing on the accuracy of speech and text processing, while communication distance tests ensure stable connectivity between base stations and IoT nodes. Through this comprehensive validation, the research findings demonstrate the efficient performance and reliability of this human-machine interaction system in IoT applications.