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| title: README | |
| emoji: 🗣️ | |
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| # SpellSpeak | |
| Models for multi-character voice experiences. | |
| They are small and fast, built to run beside a live conversation rather than in a data centre. Each one does one job well: reading how a line was said, working out who it was said to, or speaking as a character. They answer in milliseconds on a CPU or a modest GPU, so when several AI characters share one conversation, in an interactive story, a game or a voice app, each can respond like a person in the room. They run locally, inside the application that uses them. | |
| | Model | What it does | Latest release | | |
| |---|---|---| | |
| | [SpellSpeak Tone](https://huggingface.co/spellspeak/tone) | Reads one line of dialogue and says how the speaker sounds and what the line does to each person present: an emotion, a social act, how sure it is, and what the line does in the conversation | rc2.1 · 2026-10-09 | | |
| | [SpellSpeak Audience](https://huggingface.co/spellspeak/audience) | Works out who a line is for when several AI characters are listening: one of them, the whole group, or unclear, so a character can ask "Who, me?" instead of taking offence | rc2.1 · 2026-10-09 | | |
| Full precision is always there and is the reference. A release may also carry a smaller file with the usual `_fp16` suffix, with its own measured numbers on the card. Every release has a `MANIFEST.json` listing its files with checksums. | |
| Examples, demos and source: [github.com/spellspeak/models](https://github.com/spellspeak/models). Everything is under the Apache-2.0 licence. | |