Yes, there are some tools and methods that can help generate large-scale conversation data, even if these conversations may not be meaningful. Here are some options: 1. **Custom scripts**: You can write Python scripts to automatically generate large amounts of conversation data using generative language models (such as GPT-3, GPT-4). These conversations can be achieved by calling API interfaces. 2. **Markov chain**: Use the Markov chain model to generate conversations. By analyzing the corpus, the Markov chain can randomly generate sentences similar to the input text style to create conversations. 3. **Conversation generation tools**: - **Chatbot framework**: Such as Rasa, Microsoft Bot Framework, etc., help create automatic conversation systems to generate simulated user-bot conversations. - **DialoGPT**: This is a conversational version of OpenAI's GPT-2 model that can generate open-domain conversation data. 4. **Dataset generator**: Use a large language model like ChatGPT to generate conversations, and then generate and collect conversations in batches through a program loop. 5. **Open source projects**: There are many open source conversation generator projects on platforms such as GitHub, which can be modified and extended as needed to generate large amounts of data. Note that automatically generated conversational data may require additional filtering and review to ensure data quality and diversity. If the generated data is used to train machine learning models, it is also important to ensure that the data adheres to relevant ethical and legal standards.