Abstract
The Internet of Things (IoT) is currently a prominent technology, finding widespread applications across various fields. Concurrently, the fusion of speech recognition with human-computer interaction has become a critical area of research. This article focuses on the integration of these two advanced technologies, proposing an innovative approach that combines Big Data with the Internet of Things for sophisticated data mining. The core of this research involves leveraging speech recognition to enhance human-computer interaction within IoT environments, thereby improving the efficiency and accuracy of data processing. A significant contribution of this study is the development of a novel data mining model designed specifically for IoT applications, which streamlines the extraction of valuable insights from vast datasets. The research presents a detailed system architecture that illustrates the interplay between speech recognition, IoT devices, and data mining algorithms, ensuring seamless data flow and analysis. Experimental results demonstrate the efficacy of the proposed model, showcasing its ability to process complex data structures and yield meaningful patterns. This work not only advances the theoretical understanding of integrating speech recognition and IoT for data mining but also offers practical implications for developing more intuitive and intelligent IoT systems.