As the value of natural language processing in the business world becomes increasingly apparent, many organizations are adopting the technology. Many companies are utilizing big data and natural language processing to develop a variety of chatbots that extend beyond basic question-and-answer functionality. These chatbots act as a communication conduit between the customer and the business, providing real-time, targeted service. GPT-2 has unquestionably attained the pinnacle of language generation modeling in the ongoing evolution of technology. GPT-2’s transformer-based Masked Self-Attention mechanism enables it to generate a diverse range of responses contingent on the context of the sentence. These achievements are supported by a substantial quantity of data, which illustrates the pivotal role of data in the contemporary development of AI. About TTS (Text-to-Speech) and STT (Speech-to-Text) technologies, their integration into a dialog model such as ChatGPT not only provides users with a more natural interactive experience but also broadens the possibilities of ChatGPT in a variety of application scenarios to a certain extent. Consequently, this further enriches the manner of communication between humans and machines.