Real-time voice interaction AI intelligences can be quickly developed using the TEN framework by following the steps below:
- Install the TEN framework and its dependencies: make sure the system environment meets the requirements (Python 3.8+ or C/C++ compiler), clone the repository via Git and install the dependencies
- Configure speech service API: integrate Deepgram (speech recognition) and Elevenlabs (text-to-speech) services, get the API key and fill in the configuration file.
- Use the TEN Agent module: select a language model such as Google Gemini after startup, and realize a full-duplex voice conversation via microphone input
- Test interaction function: Trigger a voice command such as "tell an adventure story", the system will generate a real-time voice response and generate a supporting image through StoryTeller extension.
The entire process leverages the modular design of the framework, which can dramatically shorten the development cycle. For lightweight applications, the functionality can also be quickly verified directly using the pre-built Playground examples.
This answer comes from the articleTEN: An open source tool for building real-time multimodal speech AI intelligencesThe
May not be reproduced without permission:AI productivity tools " How to quickly implement the development of real-time voice interaction AI intelligences?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil