Abstract: To improve the data analysis capability of railway passenger transportation marketing, an intelligent dialogue system for railway passenger transportation marketing analysis has been developed, providing a data analysis tool based on human-machine dialogue for railway passenger transportation marketing business personnel. The system includes four main functional modules: speech recognition, natural language text processing, intelligent data mining, and intelligent response. It uses voice wake-up and speech recognition technology to aquire voice data, and converts the voice data into natural language text through neural network models. A natural language text preprocessing model is established to complete rule-based lexical and syntactic analysis methods. Then, long short-term memory neural networks is used to achieve semantic understanding and determine user intent. Bert-based Text-to-SQL model is employed to converts natural language text data into data query SQL statements and intelligent agents are constructed to complete data mining and analysis, and generates analysis results. Finally, speech synthesis and data visualization are used to convert the analysis results into reply to user.