炼铁-炼钢界面铁运任务语音识别技术的研究与应用OA

With the widespread application of intelligent technologies across various industries,the potential of speech recognition technology in steel production has gradually gained attention.Especially in the iron transport scheduling systems at the iron-steel interface,speech recognition technology not only significantly improves the efficiency of task formulation and execution but also reduces human errors,enhancing the accuracy of production scheduling.This paper proposes a speech recognition technology for iron transport tasks that combines the Paraformer speech recognition model and the GPT-2 semantic parsing model,aiming to efficiently convert dispatchers'instructions into actionable commands and automatically execute task scheduling.Through practical application in Tangsteel New Area,the system has significantly increased scheduling response speed,reduced errors caused by manual operations,and effectively enhanced the accuracy and efficiency of production scheduling tasks.This paper provides a detailed introduction to the model principles,architecture design,workflow,and application effects of this speech recognition technology,explores its vital role and future prospects in Tangsteel's iron transport scheduling,and offers practical support for the intelligent and green development of steel enterprises.