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Onsei-iOS-Models

Text-to-Speech
Core ML
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ios
on-device
irodori-tts
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metadata 
license: other
language:
  - ja
pipeline_tag: text-to-speech
tags:
  - coreml
  - onnx
  - ios
  - on-device
  - irodori-tts

Onsei iOS ONNX and Core ML Model Packs

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

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

Packs

  • v4.1-small-mf/: MeanFlow-distilled v4.1 Small. It preserves text, Voice Design, reference-audio cloning and duration conditioning while using one conditional DiT evaluation per step. The app defaults to four steps and ignores RF-only CFG, sway, rescale and speaker-KV controls.
  • v4.1-small/: unified Japanese TTS, reference cloning and VoiceDesign, with the improved v4.1 duration predictor. text_encoder.onnx contains the shared ModernBERT backbone and both text_state and caption_state outputs. The app reuses one session for both inputs. No separate caption_encoder.onnx is needed. Requires the v4.1-compatible iOS client.
  • 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 weights, Japanese Semantic-DACVAE adaptations, ModernBERT-ja-310m encoder/tokenizer and conversion code declare MIT. The underlying Meta DACVAE weights/implementation declare Apache License 2.0; Descript DAC uses MIT. The legacy llm-jp tokenizer uses 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}
}

Native GPU decoder (ios-v3 and later)

The v4 packs contain the verified float32 Core ML decoder. New clients download it together with the ONNX pack and verify each file using SHA-256. The app measures CPU/GPU speed and numerical parity on the device before selecting the faster decoder. Existing immutable release tags remain unchanged. The sidecar includes licenses, attribution and conversion notices.