| --- |
| language: |
| - en |
| - es |
| - fr |
| - hi |
| - it |
| - pt |
| - zh |
| license: apache-2.0 |
| library_name: transformers |
| pipeline_tag: text-to-speech |
| tags: |
| - text-to-speech |
| - tts |
| - multilingual |
| - speecht5 |
| - kokoro |
| - sol |
| --- |
| |
| # Sol |
|
|
| **Sol** is an open text-to-speech engine: type text, get clear speech. |
|
|
| It comes in two parts: |
|
|
| 1. **The live engine** — a multilingual, multi-voice TTS service running on |
| [Kokoro-82M](https://huggingface.co/hexgrad/Kokoro-82M) with **49 voices across |
| 8 languages**. Self-hosted, CPU-only, and reachable 24/7. |
| 2. **Sol v1** — a `SpeechT5` acoustic model we fine-tuned on public |
| LibriSpeech voice data, whose weights live in **this repository**. |
|
|
| **Live demo:** <https://sol-tts.vercel.app> — type a prompt and hear it speak. |
|
|
| ## Voices & languages |
|
|
| | Language | Code | Voices | |
| |---|---|---| |
| | English (US) | `en-us` | 20 | |
| | English (UK) | `en-gb` | 8 | |
| | Chinese (Mandarin) | `zh` | 8 | |
| | Hindi | `hi` | 4 | |
| | Spanish | `es` | 3 | |
| | Portuguese (Brazil) | `pt-br` | 3 | |
| | Italian | `it` | 2 | |
| | French | `fr-fr` | 1 | |
|
|
| **49 voices total.** Voice ids look like `af_heart` (American female), `am_michael` |
| (American male), `bf_emma` (British female), `ef_dora` (Spanish female), and so on. |
|
|
| ## Use the live API |
|
|
| ```bash |
| curl -X POST "$SOL_API/api/tts" \ |
| -H "Content-Type: application/json" \ |
| -d '{"text":"hello from sol","voice":"af_heart","speed":1.0}' \ |
| --output sol.wav |
| ``` |
|
|
| | Endpoint | Method | Purpose | |
| |---|---|---| |
| | `/api/health` | GET | service status | |
| | `/api/languages` | GET | supported languages + voice counts | |
| | `/api/voices` | GET | every voice (optional `?lang=en-us`) | |
| | `/api/tts` | POST | `{text, voice, speed}` → `audio/wav` (24 kHz) | |
|
|
| Audio is silence-trimmed and peak-normalised, so output is clean with no static. |
|
|
| ### Multilingual samples |
|
|
| A sample in each language lives in |
| [`examples/multilingual/`](./examples/multilingual): |
|
|
| <audio controls src="examples/multilingual/en-us.wav"></audio> |
| <audio controls src="examples/multilingual/es.wav"></audio> |
| <audio controls src="examples/multilingual/zh.wav"></audio> |
|
|
| ## Sol v1 — the fine-tuned SpeechT5 model |
|
|
| This repository also ships **Sol v1**, a `SpeechT5` model fine-tuned on a |
| single-speaker subset of [LibriSpeech](https://www.openslr.org/12) (87 utterances, |
| light fine-tune, lr 2e-6) and paired with the `speecht5_hifigan` vocoder. |
|
|
| ```python |
| import numpy as np, soundfile as sf, torch |
| from transformers import SpeechT5ForTextToSpeech, SpeechT5HifiGan, SpeechT5Processor |
| |
| repo = "itriedcoding/Sol" |
| |
| processor = SpeechT5Processor.from_pretrained(repo) |
| model = SpeechT5ForTextToSpeech.from_pretrained(repo) |
| vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan") |
| |
| speaker = torch.tensor(np.load("speaker_embedding.npy")).unsqueeze(0) |
| |
| inputs = processor(text="hello, i am sol.", return_tensors="pt") |
| with torch.no_grad(): |
| speech = model.generate_speech(inputs["input_ids"], speaker, vocoder=vocoder) |
| |
| sf.write("sol.wav", speech.numpy(), samplerate=16000) |
| ``` |
|
|
| > Keep the speaker embedding at its original scale — it is a raw x-vector with |
| > norm ≈ 320. Do **not** unit-normalise it, or the voice degrades. |
|
|
| ## Self-hosting |
|
|
| The engine is served from a FastAPI app (`server/app.py`) that loads Kokoro-82M |
| locally and exposes the endpoints above on `127.0.0.1:8000`, then published with a |
| Cloudflare tunnel. It starts automatically at logon and runs without a GPU. |
|
|
| ## Intended use & limitations |
|
|
| - **Intended use:** research, prototyping, accessibility and demos. |
| - **Limitations:** 8 languages; may mispronounce rare names, numbers and unusual |
| punctuation; Japanese is not currently enabled (G2P dependency). |
| - Output is not a human voice and must not be used for impersonation or deceptive |
| audio. |
|
|
| ## Credits |
|
|
| - Engine: [Kokoro-82M](https://huggingface.co/hexgrad/Kokoro-82M) by hexgrad. |
| - SpeechT5 v1 voice data: [LibriSpeech](https://www.openslr.org/12), CC BY 4.0. |
| - Base model & vocoder: Microsoft Research Asia, via 🤗 Transformers. |
| - Fine-tuned, hosted and packaged by the **Sol** project. |
|
|
| ## License |
|
|
| Apache-2.0. Please respect the original dataset, base-model and engine licenses. |
|
|
