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license: other
license_name: cc-by-nc-4.0-and-apache-2.0
license_link: https://huggingface.co/afrispeech/Akiti-TTS
language:
- tw
library_name: phoonnx
pipeline_tag: text-to-speech
tags:
- onnx
- tts
- twi
- akan
- neutts
- neucodec
base_model:
- afrispeech/Akiti-TTS
- neuphonic/neucodec-onnx-decoder-int8
---
# phoonnx-neutts — Akiti-TTS (Asante Twi), ONNX
ONNX conversion of [afrispeech/Akiti-TTS](https://huggingface.co/afrispeech/Akiti-TTS),
an Asante Twi text-to-speech model, packaged for
[phoonnx](https://github.com/TigreGotico/phoonnx). This repository holds converted
weights only — no new training was done.
Akiti-TTS is a LoRA fine-tune of
[pnnbao-ump/VieNeu-TTS-0.3B](https://huggingface.co/pnnbao-ump/VieNeu-TTS-0.3B), which
comes from Neuphonic's NeuTTS Air family: a Qwen3 causal LM that emits
[NeuCodec](https://huggingface.co/neuphonic/neucodec) audio tokens.
## Files (`akiti-twi-onnx/`)
| File | What it is |
|---|---|
| `neutts_lm.onnx` + `neutts_lm.onnx.data` | Qwen3 backbone, fp32, KV-cached. **The graph needs its `.data` sidecar next to it.** |
| `neutts_lm_int8.onnx` | The same graph, dynamically quantized to int8. Smaller, but measurably lower quality — it puts the end-of-speech token in the top 5 at the first step, where fp32 does not. |
| `neucodec_decoder.onnx` | Copy of [neuphonic/neucodec-onnx-decoder-int8](https://huggingface.co/neuphonic/neucodec-onnx-decoder-int8) (Apache-2.0), unmodified. |
| `tokenizer.json` | The checkpoint's own BPE, copied from upstream. |
| `voices.json` | The nine voice presets, copied from [AfriSpeech/akiti-tts](https://github.com/AfriSpeech/akiti-tts) (MIT). |
| `neutts_onnx_meta.json` | Architecture summary written by the export script. |
## Graph contract
`neutts_lm.onnx` serves prefill and decode: the same graph with a different past length.
```
inputs input_ids int64 [1, S] prompt tokens, or 1 token per step
attention_mask int64 [1, P + S] ones over past and current tokens
position_ids int64 [1, S] absolute positions, P .. P+S-1
past_key_<i> fp32 [1, 4, P, 64] i in 0..27
past_value_<i> fp32 [1, 4, P, 64]
outputs logits fp32 [1, 66938] last position only
present_key_<i> / present_value_<i> fp32 [1, 4, P + S, 64]
```
`neucodec_decoder.onnx` takes `codes` int32 `[1, 1, N]` and returns `audio` float32
`[1, 1, 480 * (N - 1)]` at 24 kHz — 50 codec tokens per second of audio.
## Prompt format
The LM is prompted with phonemes, not letters. Text is phonemized by espeak-ng using the
**`lfn`** (Lingua Franca Nova) voice, which is what the checkpoint was trained with;
espeak-ng has no Twi voice, and `lfn`'s five-vowel orthography reads Twi spelling closely.
```
<|TEXT_PROMPT_START|>{reference phones} {target phones}<|TEXT_PROMPT_END|>
<|SPEECH_GENERATION_START|>{<|speech_c|> for c in reference codes}
```
Generation continues that speech-token run until `<|SPEECH_GENERATION_END|>` or EOS.
## Fidelity
Exported with `scripts/conversion/neutts/export_neutts_onnx.py` in phoonnx. Against the
torch model on a fixed prompt, max absolute logit difference:
| | fp32 ONNX |
|---|---|
| prefill | 4.10e-05 |
| decode (8 steps) | 2.96e-05 |
The fp32 graph's top-5 next tokens on a real prompt are identical to torch's, in the same
order and to two decimal places.
## Licensing
The pieces carry different licenses, and one of them is inconsistent upstream. Read this
before using the model.
- **`afrispeech/Akiti-TTS` weights** — the Hugging Face model card declares
**CC BY-NC 4.0** (non-commercial). The
[GitHub README](https://github.com/AfriSpeech/akiti-tts) instead states the weights are
Apache-2.0. These two statements disagree. This mirror records both and resolves
neither; treat the stricter of the two (**non-commercial**) as binding until AfriSpeech
clarifies. The GitHub repository's *code* is MIT, which is not in dispute.
- **`neucodec_decoder.onnx`** — Apache-2.0, from Neuphonic.
- **`voices.json`** — from the MIT-licensed AfriSpeech/akiti-tts repository.
Attribution: AfriSpeech / Ghana NLP (Akiti-TTS), pnnbao-ump (VieNeu-TTS-0.3B), Neuphonic
(NeuTTS Air, NeuCodec).
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