| --- |
| license: cc-by-nc-sa-4.0 |
| base_model: magma90909/vocence_miner_v7 |
| pipeline_tag: text-to-speech |
| library_name: transformers |
| language: |
| - en |
| tags: |
| - tts |
| - prompttts |
| - qwen3-tts |
| - voice-design |
| - vocence |
| - british-english |
| - uk-accent |
| --- |
| |
| # vocence_miner_v8 |
|
|
| A naturalness-first prompt-driven TTS, built on top of `magma90909/vocence_miner_v7`. Two things distinguish this checkpoint: |
|
|
| * **British English coverage.** Phrasings like *"A man with a British English accent"*, *"A Scottish woman, conversational"*, *"a Welsh narrator"* land on a real distribution rather than slipping back to neutral US English. |
| * **Conversational subtlety.** Tuned for everyday delivery — *"speaking warmly"*, *"softly sad"*, *"with a touch of anger, controlled"* — rather than theatrical intensity. The model deliberately steps back when you don't ask for drama. |
|
|
| 24 kHz mono WAV output, single forward call, no reference audio, no PEFT runtime. Everything ships in this repo. |
|
|
| ## Generate |
|
|
| ```bash |
| pip install qwen-tts transformers torch soundfile |
| ``` |
|
|
| ```python |
| from qwen_tts import Qwen3TTSModel |
| import soundfile as sf |
| |
| m = Qwen3TTSModel.from_pretrained("magma90909/vocence_miner_v8") |
| |
| wavs, sr = m.generate_voice_design( |
| text="The train to Edinburgh departs from platform four.", |
| instruct="A man with a British English accent, calm and natural.", |
| language="english", |
| ) |
| sf.write("out.wav", wavs[0], sr) |
| ``` |
|
|
| `demo.py` walks through three preset prompts. |
|
|
| ## How to write `instruct` |
|
|
| The model responds best to **subtle, conversational** language — not intensifiers like *"intensely sad"* or *"nearly shouting"*. Stack these elements freely: |
|
|
| | Layer | Phrasings | |
| |-------|-----------| |
| | Accent / region | *British English*, *Scottish*, *Welsh*, *Northern Irish*, *Irish*, *unspecified* | |
| | Gender | *a man*, *a woman*, *a British woman* | |
| | Mood | *speaking warmly*, *softly sad*, *quietly pleased*, *with a touch of anger* | |
| | Persona | *bedtime storyteller, soft and warm*; *news anchor, professional and neutral*; *meditation guide, soft and serene* | |
| | Pace | *unhurried*, *brisk steady*, *naturally measured* | |
|
|
| Some example prompts that work well: |
|
|
| ``` |
| A British man speaks calmly and naturally. |
| A woman with a Scottish accent, in an everyday speaking tone. |
| A man, softly sad, calm and unhurried. |
| A British news anchor, professional and neutral, at a brisk steady pace. |
| A clear, neutral voice reading the sentence. |
| ``` |
|
|
| ## Best-fit and not-fit |
|
|
| **Best at:** |
| * Natural, everyday English — both US and UK |
| * Bedtime storyteller / news anchor / meditation guide style reads |
| * Conversational sadness, warmth, mild anger, gentle pleasure |
|
|
| **Less suited for:** |
| * Theatrical / caricatured delivery (loud anger, shouted joy, dramatic sadness) |
| * Extreme intensifier prompts ("nearly shouting", "intensely sad") — the model intentionally tones these down |
| * Languages other than English |
|
|
| CC BY-NC-SA 4.0 — research and non-commercial use only. |
|
|
| ## Files |
|
|
| ``` |
| model.safetensors # merged Talker weights (3.6 GB) |
| speech_tokenizer/ # Qwen3 12 Hz audio codec (~650 MB) |
| tokenizer.json + ... # text tokenizer |
| config.json + ... # model configs |
| miner.py # Vocence engine |
| chute_config.yml # Chutes build (TEE / pro_6000) |
| vocence_config.yaml # runtime knobs |
| demo.py # quick smoke test |
| ``` |
|
|
| The Vocence files make this repo deployable on **Bittensor SN78 (Vocence)** via the canonical Vocence/Chutes wrapper without modification. |
|
|
