TEN Framework: Build Conversational Voice AI Agents

Voice AI is having a moment. Real-time conversation with AI—not just text chat—is becoming practical. But building voice agents is complex: speech recognition, natural language understanding, response generation, text-to-speech, all with sub-second latency.

TEN Framework is an open-source toolkit for building real-time multimodal conversational AI.

What’s in the Ecosystem

TEN isn’t just one repo—it’s a complete stack:

• TEN Framework — Core runtime for building agents
• Agent Examples — Ready-to-use voice agent templates
• TEN VAD — Voice Activity Detection
• TEN Turn Detection — Conversation turn-taking
• Portal — Management interface

Why Voice AI is Hard

Text chatbots are (relatively) easy: process input, generate output, done.

Voice agents need:

1. Real-time STT — Convert speech to text with minimal latency
2. Interruption handling — Users don’t wait for the AI to finish
3. Turn-taking — Know when to speak vs. listen
4. Low-latency TTS — Responses must feel immediate
5. Multimodal context — Understand tone, not just words

TEN provides primitives for all of this.

Getting Started

Docker quickstart:

docker compose up

Or run locally:

git clone https://github.com/TEN-framework/ten-framework
cd ten-framework
# Follow setup instructions

The agent examples give you working voice agents out of the box that you can customize.

Use Cases

• Customer service — Voice bots that don’t feel robotic
• Assistants — Hands-free AI interaction
• Accessibility — Voice interfaces for users who can’t type
• Gaming/VR — NPCs that actually converse

My Take

Voice is the next interface frontier after text chat. OpenAI’s voice mode showed what’s possible; TEN lets you build similar experiences with open-source components.

The ecosystem approach—VAD, turn detection, framework—is smart. Voice AI requires tight integration between components. Having them designed to work together beats stitching random libraries.

Links:

• GitHub
• Discord
• HuggingFace