Self-hosted voice AI with Whisper and Kokoro
Build private voice experiences on an open stack. We connect Whisper speech-to-text, your language model and Kokoro text-to-speech into a pipeline designed for natural conversation.
Book an architecture callSee the ARIA case study
Whisper
Ollama
Qdrant
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DockerWhat is a Whisper and Kokoro voice stack?
Whisper is an open speech recognition model from OpenAI, and faster-whisper is a widely used, efficient implementation. Kokoro-82M is an open-weight text-to-speech model with 82 million parameters and an Apache 2.0 licence on its weights.
Together with a language model, they form a self-hosted voice AI stack that can keep audio on your own infrastructure. Please check dependency licences for your use: Kokoro relies on espeak-ng, which is GPLv3.
What we build with this self-hosted voice AI stack
The same components support tutors, assistants and support workflows.
Speech to text
Deploy and tune Whisper for your accents, languages and audio quality.
Text to speech
Configure Kokoro voices and language selection for natural replies.
Conversation pipeline
Connect speech, models and retrieval, with low-delay streaming.
Knowledge answers
Ground voice replies in your documents, with sources where useful.
RAG infrastructure →Telephony and apps
Integrate with web, mobile and calling systems, based on your needs.
Voice AI agents →Private hosting
Keep audio and transcripts within your network with access controls.
Private deployments →Self-hosted or managed voice services?
Self-hosted stack
Best forPrivate audio and steady, high usage
Watch forYou manage capacity, updates and quality
Managed voice APIs
Best forFast launch and premium voices
Watch forUsage cost and data leaving your environment
Hybrid
Best forSensitive transcription with selected managed services
Watch forMore integration and governance
How we deliver self-hosted voice AI
We test with real audio early, because lab recordings rarely match real conditions.
Collect
Gather sample audio and key scenarios.
Benchmark
Test transcription and voices.
Assemble
Build streaming and retrieval pipeline.
Tune
Reduce delay and improve accuracy.
Operate
Monitor quality, errors and capacity.
Self-hosted voice AI design guide
Delay shapes the experience
Self-hosted voice AI feels natural only when replies begin quickly. Total delay combines transcription, retrieval, the language model and speech generation. Streaming partial replies helps greatly, so measure each stage separately and improve the slowest one first.
Test with real audio
Clean recordings give misleading results. Test self-hosted voice AI with the phones, accents, background noise and mixed languages your users really have. Whisper model size also trades accuracy against speed, so choose based on these real samples.
Handle conversation behaviour
People interrupt, pause and change their minds. A production system needs voice activity detection, interruption handling and clear fallbacks when it is unsure. These details often matter more to users than small differences between speech models.
Protect voice data
Audio and transcripts can contain personal information. Decide what is stored, for how long and who can access it. Self-hosting keeps processing within your environment, but consent, retention and access rules still need to be designed and documented.
Official resources: OpenAI Whisper, faster-whisper and Kokoro-82M.
Self-hosted voice AI questions
Is there a live example of this stack?
Yes. ARIA, our English and Hindi study assistant, uses faster-whisper, Kokoro-82M, a hosted Qwen model and Qdrant on a private network. See the case study for measured results.
Does Whisper need a GPU?
Whisper can run on CPU, but GPUs are generally preferred for lower delay at higher usage. The right setup depends on model size and traffic.
Can Kokoro be used commercially?
Kokoro weights are published under Apache 2.0. Its stack also includes dependencies with other licences, including espeak-ng under GPLv3, so please have your legal team review them.
Which languages are supported?
Whisper supports many languages. Voice availability in Kokoro differs by language. We test the languages you need before you commit.
Related AI infrastructure and services
Plan your voice AI stack
Share your use case, languages and expected call volume, and we will map out a suitable pipeline.
Talk to our AI infrastructure team