Interactive Cycle Model -- The Linkage Combination among Automatic Speech Recognition, Large Language Models and Smart Glasses

This research proposes the interaction loop model "ASR-LLM-Smart Glasses", which model combines automatic speech recognition, large language model and smart glasses to facilitate seamless human-computer interaction. And the methodology of this research involves decomposing the interaction process into different stages and elements. Speech is captured and processed by ASR, then analyzed and interpreted by LLM. The results are then transmitted to smart glasses for display. The feedback loop is complete when the user interacts with the displayed data. Mathematical formulas are used to quantify the performance of the model that revolves around core evaluation points: accuracy, coherence, and latency during ASR speech-to-text conversion. The research results are provided theoretically to test and evaluate the feasibility and performance of the model. Although such human-computer interaction products have not yet appeared in the industry, the performance indicators of this model in enhancing user experience in fields that rely on human-computer interaction have also verified its utility as a technology to promote human-computer interaction. In addition, this research pioneered the idea of integrating cutting-edge technologies such as generative pre-trained Transformer models into unique interaction models, LLM provides raw value through powerful evaluation techniques and innovative use, which provides a new perspective to evaluate and enhanced human-computer interaction. Keywords: Automatic speech recognition, Large Language Model, Smart glasses, Interaction mechanism