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Owned by Nour

Voice AI made open: Learn to build voice agents with Livekit & Pipecat and uncover what the closed platforms are hiding.

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41 contributions to Open Source Voice AI Community
Chatterbox Turbo - Open Source Voice Model Worth Your Attention
Resemble AI just dropped Chatterbox Turbo and it's legitimately impressive. What it is: A fully open-source, MIT-licensed text-to-speech model that benchmarks ahead of ElevenLabs Turbo and Cartesia Sonic 3. Why you should care: - <150ms time-to-first-sound — fast enough for real-time applications, at least in English - Voice cloning from just 5 seconds of audio -- no lengthy training datasets needed - Paralinguistic tags — control laughs, pauses, breaths for natural human expression - MIT license — use it commercially, fork it, do whatever you want!! The model is designed to be transparent and auditable, which matters if you're building anything that needs to prove authenticity or pass compliance checks. GitHub repo: https://github.com/resemble-ai/chatterbox If you've been looking for a serious open-source alternative to the paid voice APIs, this is worth testing. The 5-second cloning alone makes it interesting for rapid prototyping. Anyone already running this locally? Curious about real-world latency and quality compared to the benchmarks. Share your ideas and results
0 likes • 21d
Tried it. Starts to talk gibberish when you send more than two sentences... Or am I doing something wrong? The non turbo one is good though
Welcome Chris from the LiveKit Team
I’m excited to share that another member of the LiveKit team has joined the party! Please join me in welcoming @Yepher Yepher from LiveKit’s Developer Relations team!
1 like • Dec '25
@Yepher Yepher Glad to have you here, Yepher, and thank you for your contributions. I’ve read them all and always find your insights helpful. We should chat about aviation sometime 😄 I think I’ve watched just about every Mayday episode out there.
open source outbound AI
Is there any fully free, open-source method to make outbound AI voice calls? If anyone has an idea or experience with this, please share.
2 likes • Nov '25
You can use Pipecat or LiveKit for the orchestration. For the models, you can use on open-source options such as Whisper for STT, Llama for the LLM, and Piper for TTS. However, open-source models generally don’t perform as well as commercial ones. On top of that, you need GPU servers to achieve acceptable latency, which typically start at around $700 USD. In short, it’s not currently feasible to build and maintain production-grade voice AI agents entirely for free. Another approach is to make the most of free-tier cloud credits.For example, in this video I showcase a multilingual agent that loops through Groq’s LLMs and uses only the free credits: https://www.youtube.com/watch?v=mhh3QNf6gwl In another video, I show how to use Deepgram for TTS and STT, since they provide $200 in free credits, which can last quite a while: https://www.youtube.com/watch?v=_dIYv9YdT5s
How I build production voice AI systems (workflow adopted by $4B unicorn engineering team)
Made a video walking through the AI-assisted development workflow I use for production voice AI projects. Quick context: I used this on a Vapi replacement project at a $4 billion unicorn. Within a couple of weeks, their engineering team had adopted the workflow without being asked — and they wanted me to present it division-wide. The video covers: - How I coordinate specialised AI agents for Pipecat, Vapi, and Twilio research - Building features that would normally take hours of documentation reading - Live implementation of JSON-based assistant configuration (swap providers via config file, no code changes) https://youtu.be/AG68VC_mOGY Happy to answer questions.
1 like • Nov '25
Thanks for sharing John! This is really helpful!
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Nour aka Sanava
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@nour-ogl-7836
Voice AI Educator & Developer

Active 3m ago
Joined Sep 15, 2025
Cyprus