---
license: apache-2.0
language:
- en
pipeline_tag: text-to-speech
library_name: onnx
base_model:
- hexgrad/Kokoro-82M
- gradium/phonon-31m-en
- sahilmahendrakar/Paradee-8M-v1.1
tags:
- text-to-speech
- tts
- onnx
- webassembly
- wasm
- on-device
- browser
- cpu
- tiny
- distillation
- kokoro
- phonon
widget:
- text: "This is where the page began: one small voice, made right here in your browser, faster than you can blink."
example_title: "Heart · US female"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/heart.mp3
- text: "No server is reading this to you. Every word is being made on your device, as you listen."
example_title: "Wren · US female"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/wren.mp3
- text: "Take a breath and settle in. I can read you anything you like, as slowly as you like."
example_title: "Everly · US female"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/everly.mp3
- text: "Your text never leaves this tab. It turns into speech right here, in a few milliseconds."
example_title: "Hadley · US female"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/hadley.mp3
- text: "Put the kettle on, find a comfy chair, and I'll read you the next chapter."
example_title: "Bryony · UK female"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/bryony.mp3
- text: "Right, let's get straight to it. Tell me what to say, and I'll say it with a smile."
example_title: "Maeve · UK female"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/maeve.mp3
- text: "Give me a headline, and I'll make it sound like the most important news of the day."
example_title: "Miles · US male"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/miles.mp3
- text: "Hey, I'm running in your browser right now, and honestly? I'm having a great time."
example_title: "Trevor · US male"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/trevor.mp3
- text: "Good evening. Shall we begin? I'll be narrating tonight's story, clearly and precisely."
example_title: "Edwin · UK male"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/edwin.mp3
- text: "Lean in a little. I'll keep it gentle, and I'll keep it short."
example_title: "Hugh · UK male"
output:
url: https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/hugh.mp3
---
# mesm-tts: ten tiny English voices, 100 to 300 times faster than real time on one CPU core
Ten English text-to-speech voices, small enough to ship in a web page and fast enough to stream on one CPU core. No GPU, no
server, and no onnxruntime in the browser: a 40 kB WebAssembly engine runs them. Try all ten in the
[mesmer.tools TTS Generator](https://mesmer.tools/free-tools/tts-generator).
| | |
|---|---|
| **Size** | 2.3 to 6.9 MB per voice, vs. 325 MB (Kokoro-82M) and 55 to 103 MB (Phonon-31m-en) |
| **Native, 1 CPU core** | Heart **234x to 292x** real time (about 150x to 180x faster than Kokoro-82M); Phonon voices **82x to 106x** (about 30x faster than Phonon-31m-en) |
| **Browser, 1 CPU core** | Heart **149x to 201x**, Phonon voices **55x to 80x**; first audio after 10 to 55 ms |
| **Memory** | 100 to 117 MB peak for the whole process (Heart), vs. 770 to 849 MB with onnxruntime-web; the engine is 40 kB |
| **iPhone 13 Pro** | about **50x** real time (Heart), about **33x** (Phonon voices) |
| **Quality** | Heart: UTMOS 4.46, WER 5.6% (Kokoro-82M: 4.52, 5.7%). Every Phonon voice is statistically tied with its teacher on WER |
## Listen
Each voice reading its own line, as a browser tab plays it.
Voice
Sample
Heart · US female · the default
Wren · US female · Phonon's built-in
Everly · US female · soft
Hadley · US female · calm
Bryony · UK female · warm
Maeve · UK female · bright
Miles · US male · resonant
Trevor · US male · lively
Edwin · UK male · crisp
Hugh · UK male · gentle
**Student vs. original.** The same passage, read by each small model and by its teacher:
> *The lighthouse keeper climbed the stairs one last time. Below him, the harbor lights blinked awake, one by one, and the
> evening ferry sounded its horn. He had kept this light burning for thirty-one years. Tonight, for the first time, he wasn't
> sure he was ready to let it go.*
Voice
Read by
Sample
Heart
mesm-tts
Kokoro-82M
Wren
mesm-tts
Phonon-31m-en
Everly
mesm-tts
Phonon-31m-en
Hadley
mesm-tts
Phonon-31m-en
Bryony
mesm-tts
Phonon-31m-en
Maeve
mesm-tts
Phonon-31m-en
Miles
mesm-tts
Phonon-31m-en
Trevor
mesm-tts
Phonon-31m-en
Edwin
mesm-tts
Phonon-31m-en
Hugh
mesm-tts
Phonon-31m-en
No model saw this passage in training, and each original is level-matched to its student. For reference:
[Paradee-8M v1.1 reading it](https://huggingface.co/mesmertech/mesm-tts/resolve/main/samples/passage/heart_paradee_v1.1.mp3),
the model Heart started from.
## The voices
| Voice | Learned from | ONNX file | Native | Browser |
|---|---|---:|---:|---:|
| **Heart** lite (default) | Kokoro-82M `af_heart` | 2.64 MB | **274x** | **185x** |
| Heart v2f (best scores) | | 3.42 MB | 234x | 149x |
| Heart v2g (streams first) | | 2.32 MB | **292x** | **201x** |
| **Wren** | Phonon-31m-en, built-in voice | 5.34 MB | 105x | 80x |
| **Everly, Hadley, Bryony, Maeve, Miles, Trevor, Hugh** | Phonon-31m-en + phonon-voices | 5.34 MB | 104x to 106x | 80x |
| **Edwin** | | 6.50 MB | 82x | 55x |
x real time on 1 core: onnxruntime 1.31 natively; pdn relaxed SIMD in Chrome and Edge (Firefox and Safari: 70 to 85% of that).
## Quick start
### Python
```bash
pip install -r requirements.txt # about 0.5 GB, no PyTorch
python tts.py "Hello there. How are you?" --voice hadley --out hello.wav # --list for voices; Heart takes --model v2g
```
```python
from tts import MesmTTS # downloads the voice's ONNX file on first use
tts = MesmTTS("miles")
audio = tts.synth("Good evening.") # float32, 24 kHz
tts.save("Good evening.", "evening.wav")
```
### Browser, no install
```html
```
Heart uses the `v2` bundle: `loadParadee({ model: "v2f_lite" })` from `https://mesmer.tools/paradee/v2/paradee.mjs`. To
self-host, serve the repo root with `python -m http.server 8000` and open `http://localhost:8000/web/demo.html`. Bundlers and
workers: [`web/v2/README.md`](web/v2/README.md).
### Node, no dependencies
```bash
node web/say.mjs "Good evening. Shall we begin?" evening.wav edwin # --list for voices
```
### Raw ONNX
Every file in `onnx/` has Paradee-8M v1.1's interface:
| name | type | |
|---|---|---|
| `input_ids` (in) | int64 `[1, T]` | `0`, phoneme ids (`tokenizer.json`), `0`; T ≤ 512 |
| `speed` (in) | float32 `[1]` | 1.0 = trained rate |
| `waveform` (out) | float32 `[1, samples]` | mono, 24 kHz |
```python
import numpy as np, onnxruntime as ort
s = ort.InferenceSession("onnx/voices/hadley.onnx", providers=["CPUExecutionProvider"])
wav = s.run(None, {"input_ids": ids, "speed": np.ones(1, np.float32)})[0][0] # ids: np.int64 [1, T]
```
## Benchmarks
Both images are drawn by `assets/make_images.py` from the repo's own samples and benchmark files; teachers' speeds are scaled
from interleaved runs. Full tables and protocols: [`benchmarks/README.md`](benchmarks/README.md).
### Native speed (onnxruntime 1.31, 1 thread)
| Model | x real time | vs. Paradee-8M v1.1 |
|---|---:|---:|
| Paradee-8M v1.1 int8 | 42.3 | 1.00 |
| **Heart v2g** | **291.5** | **6.89x** |
| **Heart v2f lite** | **273.8** | **6.47x** |
| Heart v2f | 234.1 | 5.53x |
| Phonon voices (Edwin) | 104.1 to 105.8 (82.0) | 2.46x to 2.50x (1.94x) |
Teachers, same core: Kokoro-82M (PyTorch) 1.04x real time, Phonon-31m-en (f32) 1.7x to 2.9x.
### Browser speed (1 thread, V8)
| Model | onnxruntime-web | pdn (relaxed SIMD) | First audio | Cold start |
|---|---:|---:|---:|---:|
| Paradee-8M v1.1 | 15.1x | | | 3.6 s |
| **Heart v2g** | 96.5x | **201.3x** | **10 ms** | **60 ms** |
| **Heart v2f lite** | 84.8x | **185.2x** | 20 ms | 75 ms |
| Heart v2f | 73.4x | 148.7x | 29 ms | 84 ms |
| Phonon voices (Edwin) | | 80.0x (54.7x) | 55 ms | 111 to 115 ms |
Peak process memory for Heart: 100 to 117 MB with pdn (38 to 40 kB brotli) and 770 to 849 MB with onnxruntime-web.
### Phones
| Device | Heart | Phonon voices | v1.1 on onnxruntime-web |
|---|---:|---:|---:|
| **iPhone 13 Pro**, Safari (live page, measured by hand) | **~50x** | **~33x** | |
| Desktop core slowed about 6x (low-end phone proxy) | 32x (v2g) | | 2.6x |
### Quality: Heart (TEST-200, held out, 3 seeds)
| | Paradee-8M v1.1 | Heart v2f | Heart v2f lite | Heart v2g | Kokoro-82M |
|---|---:|---:|---:|---:|---:|
| UTMOS ↑ | 4.391 | **4.462** | 4.453 | 4.453 | 4.520 |
| WER ↓ | 5.85% | 5.65% | 5.64% | **5.48%** | 5.67% |
| WER, capped ↓ | 5.17% | 4.91% | **4.84%** | 4.91% | |
Heart is significantly more natural than v1.1 (UTMOS +0.06 to +0.07) and statistically tied with v1.1 and Kokoro-82M on WER.
### Quality: Phonon voices (DEV-400, vs. their own teachers)
| Voice | UTMOS, student / teacher | WER, student / teacher | Capped WER, student − teacher, 95% CI (pp) |
|---|---:|---:|---:|
| Wren | 4.417 / 4.452 | 6.24% / 6.11% | [−0.26, +0.61] |
| Everly | 4.346 / 4.434 | 6.09% / 6.12% | [−0.54, +0.29] |
| Hadley | 4.469 / 4.496 | 5.98% / 6.10% | [−0.41, +0.51] |
| Bryony | 4.172 / 4.331 | 6.95% / 7.43% | [−0.78, +0.21] |
| Maeve | 4.391 / 4.442 | 6.31% / 6.20% | [−0.39, +0.59] |
| Miles | 4.258 / 4.365 | 6.17% / 6.45% | [−0.49, +0.36] |
| Trevor | 4.323 / 4.425 | 6.23% / 6.17% | [−0.30, +0.55] |
| Edwin | 4.216 / 4.389 | 6.05% / 6.16% | [−0.56, +0.34] |
| Hugh | 4.267 / 4.367 | 6.83% / 6.58% | [−0.35, +0.64] |
No capped-WER difference is significant. DEV-400 is held out but was used for model selection, so these are development numbers.
### How we tested
- **Texts:** TEST-200, the 200 held-out WikiText-103 sentences on Paradee-8M v1.1's card ([source](https://github.com/sahilmahendrakar/paradee)), looked at once per release; DEV-400 for selection; XDEV-1600 for small WER gaps.
- **WER:** Whisper-base, also capped at 3 errors per sentence, with Whisper large-v3-turbo as a guard.
- **Naturalness:** UTMOS22-strong, a MOS predictor, not a listening test.
- **Significance:** paired per-sentence bootstrap; a difference counts only if its 95% CI excludes zero and it beats seed noise.
- **Speed:** one reserved i7-14700K P-core at 4.5 GHz, 1 thread, interleaved with the baseline, median of 3 rounds.
## How it was made
A team of AI coding agents, run from [T3 Code](https://t3.codes), built the models, the engine and the evaluation harness in
about a week on one desktop GPU. An orchestrator wrote the brief (*"Beat Paradee-8M v1.1 on all three axes at once: faster,
smaller, and better"*) and spawned specialist agents; the human set goals, listened, and decided. Short prompts changed course:
- *"The final model runs in the browser, on mobile and laptop."* Speed was judged in the browser from then on.
- *"Think beyond the runtime."* onnxruntime-web's 21.6 MB WASM dwarfed a 3 MB model, so an agent wrote pdn.
- *"Add more voices: four female, four male."* Seven more Kokoro voices passed the agents' checks, but the human found them
*"not good enough"*, so the project switched teachers to Phonon-31m-en.
The rules: TEST was never used to choose, and every gain had to clear seed noise.
## Files
| Path | What |
|---|---|
| `onnx/heart/`, `onnx/voices/` | Heart's `v2f_lite`, `v2f`, `v2g` (int8 math; `*_noint8` twins: fp32 math), and the nine Phonon voices |
| `web/` | the browser bundle mesmer.tools serves: `v2/` (Heart), `pv/` (Phonon voices), `voices/*.pdn`, `demo.html`, `say.mjs` |
| `tts.py`, `voices.json` | Python inference; per-voice files, sha256, level, joins, quality |
| `samples/`, `assets/`, `benchmarks/` | the clips above, the images, full benchmark tables and raw JSON |
## Limitations
- English only: US-English misaki phonemes, the UK voices too.
- Below the teachers: Heart about 0.06 UTMOS under Kokoro, the Phonon voices 0.03 to 0.17 under Phonon. No human MOS study.
- Rare words (about 3.5% of DEV words) need eSpeak NG (GPL-3.0, not included).
- At most 512 phoneme ids (roughly 25 s) per call; longer sentences are split.
- Not bit-reproducible: the models draw their own noise.
- Speeds come from one desktop core; the iPhone figure was measured by hand.
## Responsible use
Don't use these synthetic voices to impersonate real people or mislead listeners; disclose synthetic speech.
## License and credits
Apache-2.0 (`LICENSE`, `NOTICE`) covers the models, the engine and all code here. Built on these Apache-2.0 projects:
- [Kokoro-82M](https://huggingface.co/hexgrad/Kokoro-82M) by hexgrad: Heart's teacher (`af_heart`).
- [Paradee-8M v1.1](https://huggingface.co/sahilmahendrakar/Paradee-8M-v1.1) by Sahil Mahendrakar: Heart builds on it and its
[training code](https://github.com/sahilmahendrakar/paradee).
- [Phonon-31m-en](https://huggingface.co/gradium/phonon-31m-en) and [phonon-voices](https://huggingface.co/gradium/phonon-voices)
by Gradium: the teachers of the other nine voices. Phonon builds on Kyutai's [Pocket TTS](https://github.com/kyutai-labs/pocket-tts)
and the Mimi codec. This repo contains no Phonon, Pocket TTS or Mimi weights, and we used only the Apache-2.0 31m model, not
the CC BY-NC 40m models.
- [misaki](https://github.com/hexgrad/misaki) by hexgrad: the phonemizer, ported to JavaScript in `web/*/frontend/`.
Built by [mesmer.tools](https://mesmer.tools).