Abstract: The lexicon quality affects the performance of Chinese language model directly. However, the lexicon compilation is separated from Chinese language modeling, resulting in two severe problems: Firstly, the current language models can not achieve the optimal performance due to the limitation of lexicon scale; secondly, it's hard to apply the current language models to special areas due to the absence of lexicon. Our works aim to improve the performance of Chinese language model by constructing optimal lexicon. In the meanwhile, it can self-adapt the area of training corpus automatically. From the experimental results, it is found that the system can obtain the optimal Chinese lexicon as well as the high-performance Chinese language model. Moreover, the proposed techniques can self-adapt the area of training corpus successfully.