Design and Application System of Machine Translation Language Model Based on Cloud LM Algorithm

Language modeling is the core of natural language processing, especially in areas such as speech recognition and machine translation. This article is based on Cloud LM (Cloud Language Model), using Apache Solr as the platform, and cloud computing as the foundation, with the goal of improving the efficiency and scalability of machine translation. This article designed an open-source cloud environment management platform that enables users to quickly and effectively retrieve distributed language models, while also achieving real-time updates and maintenance of the models. Through comparative experiments, research and analysis were conducted on the translation efficiency, network latency, and resource utilization based on Cloud LM. Even when processing translation tasks of up to 1000 sentences, the CPU (Central Processing Unit) usage and memory consumption of the model remained within a reasonable range. The research findings of this article contribute to improving the efficiency of machine translation work and applying it for scalability and practicality in cloud computing environments, providing strong technical support for future fields such as machine translation.