A guide to realizing realistic multi-round conversations
Achieving realistic multi-round conversations with Linly-Talker digital people relies heavily on its integrated contextualization system and multiple AI technologies. Below are the steps to do so:
- environmental preparation: First make sure you have completed the project installation, including cloning the GitHub repository, installing dependencies (pip install -r requirements_app.txt) and environment configuration
- Activation of the dialog system: Launch the web interface by running python webui.py, visit http://localhost:7860
- Dialog mode selection: Select the "Multi-Round Dialog" function module in the WebUI, the system has enabled the context memory function by default.
- Ongoing conversation skills::
- Avoid frequent topic switches and keep the conversation consistent
- Appropriate references to the preceding text (e.g., "What we just said...") can enhance the contextualization of the system
- Conversation intervals of no more than 5 minutes to avoid a system reset context
- Enhancing authenticity::
- Uploading images of people can make the digital person more tangible
- Customize the voice of the digitizer using the voice cloning feature
- Turn on Microsoft TTS to choose a more natural voice type
The system integrates the conversational capabilities of Linly's Big Language Model with the visual performance of SadTalker, and ensures smooth communication through Whisper speech recognition. For professional scenarios, it is recommended to preset domain knowledge in the "Personalized Persona Generation" module, which can significantly enhance the professionalism of the conversation.
This answer comes from the articleLinly-Talker: An Intelligent Dialogue System for Digital People, Combining Big Language Modeling and Visual Modeling for a New Interactive ExperienceThe
