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thorstenvoice/kokoro-tts

By thorstenvoice

•Updated 2 months ago

German TTS in a Docker container, powered by Kokoro and finetuned on the Thorsten-Voice dataset.

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thorstenvoice/kokoro-tts repository overview

⁠Thorsten-Voice · Kokoro TTS Server

German Text-to-Speech in a Docker container, powered by Kokoro-82M⁠ and fine-tuned on the Thorsten-Voice⁠ dataset.

Send a text via HTTP and get a WAV audio file back. That's it. Kokoro-82M is a compact (82M parameter) model that runs comfortably on CPU, in real time or faster — no GPU required.

⁠Quickstart
docker run -p 8000:8000 \
  -v kokoro_cache:/data/hf-cache \
  thorstenvoice/kokoro-tts

First start: the model is downloaded automatically from Hugging Face (a few hundred MB). Subsequent starts are fast since the model is cached in the volume.

Once you see Modell geladen und einsatzbereit. in the logs, the server is ready.

⁠Generate audio
curl -X POST http://localhost:8000/tts \
     -H "Content-Type: application/json" \
     -d '{"text": "Hallo, ich bin Thorsten. Schön, dass du da bist."}' \
     --output thorsten.wav

That's all — thorsten.wav contains the synthesized speech.

⁠Options

Adjust speaking speed (must be greater than 0.0, up to 2.0; default 1.0):

curl -X POST http://localhost:8000/tts \
     -H "Content-Type: application/json" \
     -d '{"text": "Das hier wird etwas langsamer gesprochen.", "speed": 0.85}' \
     --output output.wav

Check if the server is running:

curl http://localhost:8000/health
# {"status":"ok","repo_id":"Thorsten-Voice/Kokoro","epoch":"5","device":"cpu"}

Choose a different training checkpoint (epochs 1–10, default is epoch 5):

docker run -p 8000:8000 \
  -e KOKORO_EPOCH=10 \
  -v kokoro_cache:/data/hf-cache \
  thorstenvoice/kokoro-tts

Create a docker-compose.yml:

services:
  thorsten-kokoro-tts:
    image: thorstenvoice/kokoro-tts:latest
    container_name: thorsten-kokoro-tts
    ports:
      - "8000:8000"
    environment:
      - KOKORO_EPOCH=5
    volumes:
      - kokoro_cache:/data/hf-cache
    restart: unless-stopped

volumes:
  kokoro_cache:

Then:

docker compose up -d
⁠Platforms

This image is published as a multi-arch build for linux/amd64 and linux/arm64 — it runs natively on Linux, Windows (via Docker Desktop/WSL2), and Mac (Intel and Apple Silicon), CPU-only.

⁠Model

This container uses the Thorsten-Voice/Kokoro⁠ model, a German fine-tune of hexgrad/Kokoro-82M⁠, trained using the kikiri-tts⁠ recipe by semidark on the Thorsten-Voice dataset (CC0).

Tag summary

Content type

Image

Digest

sha256:816385bad…

Size

475.3 MB

Last updated

2 months ago

docker pull thorstenvoice/kokoro-tts