ArkTTS ONNX for the phoonnx arktts engine

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,176 @@
+---
+language:
+  - yue
+  - zh
+  - nl
+  - en
+  - fr
+  - de
+  - it
+  - ja
+  - ko
+  - pl
+  - es
+license: apache-2.0
+base_model:
+  - Audio8/Audio8-TTS-Preview-0.6b
+tags:
+  - text-to-speech
+  - tts
+  - multilingual
+  - onnx
+  - phoonnx
+  - arktts
+  - voice-cloning
+pipeline_tag: text-to-speech
+library_name: phoonnx
+---
+
+# phoonnx-audio8-tts
+
+ONNX export of **[`Audio8/Audio8-TTS-Preview-0.6b`](https://huggingface.co/Audio8/Audio8-TTS-Preview-0.6b)**
+— an 11-language text-to-speech model — packaged for the
+[phoonnx](https://github.com/OpenVoiceOS/phoonnx) `arktts` engine.
+
+Upstream ships PyTorch only. These graphs were exported with
+[`scripts/conversion/arktts/export_arktts_onnx.py`](https://github.com/OpenVoiceOS/phoonnx/tree/dev/scripts/conversion/arktts),
+using the same contract and the same tensor names as the official export of the model's
+Basque fine-tune, [`itzune/zortzi-tts-onnx`](https://huggingface.co/itzune/zortzi-tts-onnx),
+so graphs from either source are interchangeable.
+
+Languages: Cantonese, Chinese, Dutch, English, French, German, Italian, Japanese, Korean,
+Polish, Spanish.
+
+## Usage
+
+```python
+from phoonnx.model_manager import TTSModelManager
+from phoonnx.voice import TTSVoice
+
+voice = TTSVoice.load(TTSModelManager().get_voice("arktts/audio8-maider/en"))
+audio = voice.synthesize("The quick brown fox jumps over the lazy dog.")
+```
+
+Voice ids are `arktts/audio8-{maider,antton}/{yue,zh,nl,en,fr,de,it,ja,ko,pl,es}`.
+
+## Files
+
+```
+slow_ar_fp16.onnx          24-layer backbone, KV-cached          (1.35 GB)
+fast_ar_fp16.onnx          4-layer depth transformer              (134 MB)
+codec_decoder_fp16.onnx    10 codebooks -> 44.1 kHz waveform      (278 MB)
+tokenizer.json             the model's own Qwen2 subword BPE
+voices/maider.json         reference codes + transcription
+voices/antton.json         reference codes + transcription
+runtime_manifest.json      precision and architecture metadata
+```
+
+## Voices, and where they come from
+
+Upstream ships **no reference voices** — Audio8 is a cloning model, and a voice is the codec
+codes of a short clip rather than an entry in a speaker table. To make it usable as a
+preset-voice engine, this mirror carries two voices encoded from the reference clips
+published in [`itzune/zortzi-tts`](https://huggingface.co/itzune/zortzi-tts):
+`voices/maider.wav` and `voices/antton.wav`.
+
+Those clips are from the **HiTZ-Aholab Basque TTS dataset** (CC BY 4.0). They condition
+**timbre, not language** — the model infers the language from the text — so both voices are
+offered for all eleven languages, and the WER table below is what they actually sound like
+in each. The clips are Basque, which is not one of Audio8's languages; that is fine for
+conditioning and is stated here so nobody has to work it out.
+
+The two checkpoints carry a byte-identical `codec.pth`, so re-encoding those clips with
+Audio8's own codec reproduces the codes upstream published for Zortzi: codebook 0 matches
+exactly, and all ten codebooks agree on 99.2 to 99.6 % of frames. The published Zortzi codes
+are shipped here for that reason — they are the reproducible artifact.
+
+To add your own voice, encode a clip offline with
+`scripts/conversion/arktts/mint_voice.py`. This mirror ships the codec **decoder** only;
+cloning at synthesis time would need the encoder, which is not exported.
+
+## What was verified
+
+Checked against the PyTorch checkpoint (float32) with
+`scripts/conversion/arktts/verify_parity.py`, over 24 lockstep greedy decode steps:
+
+| Tensor | max abs diff | greedy agreement | note |
+|---|---|---|---|
+| prompt `[1, 11, T]` | — | exact | identical to upstream's own processor output |
+| slow AR logits | 0.118 | 24/24 | |
+| slow AR hidden | 0.039 | — | |
+| fast AR logits | 1.36 | 208/216 | every miss is a tie; worst margin 0.225 |
+| codec decoder | 6.3e-4 | — | correlation 0.999999 |
+
+The fast AR is noisier here than in the official Zortzi export because the half-precision
+graph accumulates its RMS norms in half precision rather than single — the explicit
+float32 round-trip upstream writes cannot survive the fp16 converter. It changes no greedy
+decision that was not already a tie.
+
+Intelligibility, one sentence per language per voice, transcribed with
+`onnx-community/whisper-large-v3-turbo` on CPU:
+
+| Language | WER | Note |
+|---|---|---|
+| en | 0.000 | |
+| de | 0.000 | |
+| es | 0.000 | |
+| it | 0.000 | |
+| nl | 0.125 | one clip, one recogniser slip |
+| pl | 0.143 | the recogniser wrote "10" for "dziesięć" |
+| fr | 0.333 | the recogniser heard a plural subject in both clips |
+
+Cantonese, Chinese, Japanese and Korean are **not** covered by this run. Whisper is the only
+model in `onnx-asr` that claims `yue` at all, and a Whisper-only Cantonese number would say
+more about the recogniser than about the voice; when those are measured they should be
+scored by character (CER), not by word.
+
+CPU real-time factor on twelve cores: **13.1x** (Maider), **14.3x** (Antton) — slower than
+the official Zortzi graphs at 8x, because this export carries the tied embedding matrix
+twice and is not otherwise optimised. This is not a real-time model on CPU.
+
+## Licence and attribution
+
+Apache-2.0, from the base model. The model is by **Audio8**; this repository only exports
+and repackages it.
+
+The reference clips that carry the two voices are from the **HiTZ-Aholab Basque TTS
+dataset** (CC BY 4.0, [10.5281/zenodo.17952596](https://doi.org/10.5281/zenodo.17952596)),
+by way of [`itzune/zortzi-tts`](https://huggingface.co/itzune/zortzi-tts). That licence
+conditions the voices, so redistributing them *or audio generated with them* carries the
+attribution below.
+
+> The HiTZ-Aholab speech synthesis dataset was developed with funding from the Ministerio
+> para la Transformación Digital y de la Función Pública and Plan de Recuperación,
+> Transformación y Resiliencia — Funded by EU — NextGenerationEU within the framework of the
+> project ILENIA (ref. 2022/TL22/00215335), and by a grant from the Department of Culture
+> and Language Policy of the Basque Government (IKER-GAITU project).
+
+```bibtex
+@dataset{navas_hernaez_2025_17952596,
+    author    = {Navas, Eva and Hernaez Rioja, Inmaculada and Saratxaga, Ibon and
+                 Sanchez, Jon and García Romillo, Víctor and Flores Ríos, Mariana and
+                 Bellanco, Aitor},
+    title     = {{HiTZ-Aholab speech synthesis dataset in Basque}},
+    month     = dec, year = 2025, publisher = {Zenodo}, version = {1.0},
+    doi       = {10.5281/zenodo.17952596},
+    url       = {https://doi.org/10.5281/zenodo.17952596}
+}
+```
+
+## Known limitations
+
+Upstream's, carried over unchanged:
+
+- **Numbers are mispronounced** — spell them out in the text.
+- **No text normalization** — expand acronyms yourself ("TTS" as "te te ese").
+- **Sampling is required** — greedy decoding never reaches end-of-speech. The engine's
+  defaults (temperature 0.8, top-p 0.95) are upstream's.
+
+Specific to this export:
+
+- **Half precision only.** The codec decoder is the fp16 graph from
+  `itzune/zortzi-tts-onnx`, which is valid here because both checkpoints carry the same
+  `codec.pth`; it is verified above against *this* model's PyTorch codec.
+- **No codec encoder**, so cloning is an offline step.
+- **`slow_ar_fp16.onnx` is about 270 MB larger than it needs to be** — the tracer
+  materialises the tied output projection separately from the embedding table.

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runtime_manifest.json

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+{
+  "model_family": "audio8_tts",
+  "activation_dtype": "float32",
+  "slow_logits_layout": "semantic_then_eos",
+  "slow_logits_size": 4097,
+  "kv_attention_layout": "valid_prefix",
+  "max_seq_len": 2048,
+  "num_layers": 24,
+  "num_fast_layers": 4,
+  "num_codebooks": 10,
+  "n_local_heads": 2,
+  "fast_n_local_heads": 2,
+  "head_dim": 64,
+  "fast_head_dim": 64,
+  "fast_dim": 896,
+  "vocab_size": 155776,
+  "codebook_size": 4096,
+  "semantic_begin_id": 151678,
+  "semantic_end_id": 155773,
+  "eos_token_id": 151645,
+  "pad_token_id": 151643,
+  "sample_rate": 44100,
+  "codec_sample_rate": 44100,
+  "codec_frame_size": 2048,
+  "codec_hop_length": 2048,
+  "ras_window_size": 10,
+  "ras_top_p": 0.9,
+  "ras_temperature": 1.0,
+  "default_precision": "fp16",
+  "available_precisions": [
+    "fp16"
+  ],
+  "slow_models": {
+    "fp16": "slow_ar_fp16.onnx"
+  },
+  "fast_models": {
+    "fp16": "fast_ar_fp16.onnx"
+  },
+  "default_codec_precision": "fp32",
+  "available_codec_precisions": [
+    "fp32"
+  ],
+  "codec_models": {
+    "fp32": "codec_decoder_fp32.onnx"
+  }
+}

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+ "display_name": "Antton",
+ "reference_text": "Inguru hura gerrillarien esku izan da denbora luzean.",
+ "frames": 71,
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voices/maider.json

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+{
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+ "reference_text": "Aurrelaria prest dago jokatzeko.",
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