Application of Artificial Intelligence and Neural Network in Natural Language Processing

In this paper, we propose a new method combining BERT, Generative Adversarial Network (GAN) and Domain Adaptive technology. DA) natural language processing method - Bidirectional Adaptive Adversarial Network (BAAN). By combining the strengths of the three technologies, BAAN significantly improves the performance and adaptability of natural language processing tasks. Firstly, BERT's powerful language representation capability is used to provide rich semantic information for the model. Secondly, by utilizing the adversarial training mechanism between the generator and discriminator in GAN s, the model can enhance its understanding of data distribution and improve the quality of the text it generates. Finally, domain adaptive technology is introduced to make the model better adapt to the data distribution in different fields and improve the generalization ability of the model. The experimental results show that BAAN performs well in many natural language processing tasks and can capture key information in text more accurately than traditional methods. This fully confirms the effectiveness and practical application of the BAAN architecture in the field of natural language processing, presenting a new technical method for achieving more advanced cross-domain text processing capabilities.