kikiri-urdu-v1

kikiri-tts

<img src="docs/images/kikiri-tts-logo.png" alt="kikiri-tts logo" width="150">

[!NOTE] This repository was formerly named kokoro-deutsch. The Python package and the published HuggingFace model still use the old kokoro-deutsch name.

Training recipe for fine-tuning Kokoro-82M for German with a patched StyleTTS2 submodule.

What This Is

• A reproducible fine-tuning workflow (dataset prep -> Stage 1 -> Stage 2 -> voicepack extraction)
• Original scripts for data preparation and checkpoint/voicepack conversion
• A patched StyleTTS2/ submodule with the fixes required for stable Stage 2 training

What This Is Not

• Not a general-purpose Kokoro replacement repository
• Not a bundled upstream mirror of demo/, examples/, kokoro.js/, or tests/
• Not a redistributable training dataset

Start Here

I want to train my own German voice

Start with docs/TRAINING_GUIDE.md.

I am debugging training failures

Go to docs/TROUBLESHOOTING.md.

I want architecture details and compatibility notes

See docs/ARCHITECTURE.md.

Status

The end-to-end pipeline is working:

Dataset preparation -> Weight conversion -> Stage 1 -> Stage 2 -> Voicepack extraction -> KModel inference

Published Models & Voices

All checkpoints are compatible with the Kokoro-82M inference pipeline.

Base Model

dida-80b/kokoro-deutsch-hui-base is a German multi-speaker Stage 1 base model trained on ~51 hours of audio. It is not a finished single-speaker voice — use it as a starting point for training your own with docs/TRAINING_GUIDE.md.

Fine-Tuned Voices

Stage 2 single-speaker fine-tunings. Each ships with a speaker voicepack. Click the links to hear speech demos directly from HuggingFace.

German (de)

More voices and languages coming soon. Check the kikiri-tts HuggingFace organization for updates.

Running Verification Tests

To run a quick text-to-speech sanity check — e.g. after updating phonemizer packages like misaki, bumping dependencies, or making model changes — run the inference script with no arguments:

uv run scripts/test_inference.py

On first run this downloads a reference model (kikiri-tts/kikiri-german-martin) and voicepack into a local cache (test_output/.model_cache/), synthesizes the standard German phonetic test sentences, and writes the audio to test_output/. It runs on CPU automatically when no GPU is available, so it works on any machine and in CI/CD pipelines. Subsequent runs reuse the cached files.

To test a specific checkpoint or voice instead, pass explicit paths:

uv run scripts/test_inference.py \
    --model voices/kokoro_german_epoch3.pth \
    --voicepack voices/dm_daniel_epoch3.pt \
    --device cpu

Repository Layout

kokoro/              # Kokoro fork submodule (contains the `kokoro/` Python package)
StyleTTS2/           # Patched training code (git submodule: semidark/StyleTTS2)
scripts/             # Dataset prep, voicepack extraction, inference testing
configs/             # Training config(s)
docs/                # Training guide, troubleshooting, architecture notes
training/            # Local training artifacts metadata (audio excluded)

Contributing

Contributions are welcome, especially:

• Reproducible runs on public datasets
• Fine-tuning recipes for other languages
• Training stability and quality improvements

Attribution

See NOTICE for upstream attribution and license details.

License

Apache License 2.0 — see LICENSE.