README.md

metadata

license: other
language:
  - ja
pipeline_tag: text-to-speech
tags:
  - onnx
  - ios
  - on-device
  - irodori-tts

Onsei iOS ONNX Model Packs

ONNX model packs exported for the Onsei iOS client from the following upstream models:

• Aratako/Irodori-TTS-500M-v3, source revision 236c1e56591279fc24e3c1bf6609fc06e48dde28
• Aratako/Irodori-TTS-600M-v3-VoiceDesign, source revision e863a3a93e652e09afeff3e84823a206a0a60314
• Aratako/Semantic-DACVAE-Japanese-32dim
• Tokenizer from llm-jp/llm-jp-3-150m

These files are converted runtime artifacts, not new model weights. They are not affiliated with or endorsed by the upstream authors.

Packs

• 500m-v3/: standard Japanese TTS and reference-audio voice cloning.
• 600m-v3-vd/: VoiceDesign model with caption conditioning.

Each pack contains the split context_kv.onnx + dit_step.onnx execution path used by the Onsei iOS app, DACVAE encode/decode, speaker and text encoders, duration prediction, configuration, and tokenizer data. manifest.json records file sizes and SHA-256 digests used by the app to verify downloads.

Licenses and attribution

The Irodori-TTS model weights, Semantic-DACVAE model weights, and conversion code are distributed under the MIT License. The llm-jp tokenizer is distributed under Apache License 2.0. See LICENSES/ and THIRD_PARTY_NOTICES.md. Each component remains subject to its own license; no relicensing is implied.

Responsible use

The upstream model cards request that users:

1. Do not clone or impersonate a person's voice without explicit consent.
2. Do not create misleading deepfakes or synthetic speech intended to spread misinformation.
3. Recognize that text-only output may coincidentally resemble a real voice.
4. Take responsibility for compliance with applicable law.

The ONNX export used here does not add a SilentCipher watermark. Applications using these files should clearly disclose synthetic audio where appropriate and must enforce consent for voice cloning.

Citation

@misc{irodori-tts-v3,
  author = {Chihiro Arata},
  title = {Irodori-TTS: A Flow Matching-based Text-to-Speech Model with Emoji-driven Style Control},
  year = {2026},
  publisher = {Hugging Face},
  howpublished = {https://huggingface.co/Aratako/Irodori-TTS-500M-v3}
}