OuteTTS TTS
An LLM-based TTS that runs on CPU, GPU, or even in the browser via llama.cpp and Transformers.js.
Ojehaijey ñe'ẽnguéra etiquetas SSML-pe peteĩ control hekopete g̃uarã:
<speak><prosody rate="slow">Slow speech</prosody></speak>
Etiquetas ohechakuaáva modelo ojeporavóva - tesãirã peteĩ peteĩva ñe'ẽnguérape, oĩhápe:
Ko modelo ohai texto ndahasyivéva, upévare umi etiqueta oĩva línea ryepýpe ndojehechakuaái. Umi emoción oñemopyendáva etiqueta-pe g̃uarã, oñemoambue peteĩ modelo expresivo-pe taha'e Orfeo térã Bark.
Oñemohenda ñe'ẽnguéra ojehechapyréva (tembiapo = ñe'ẽnguéra):
Mba'épa OuteTTS
OuteTTS by OuteAI takes a language-model approach to speech: it extends an LLM with text-to-speech capability while keeping the original architecture intact, so it can run through standard LLM tooling. That gives it unusually broad backend support — llama.cpp on CPU or GPU, Hugging Face Transformers, ExLlamaV2, VLLM, and even in-browser inference via Transformers.js. It is a natural fit for edge deployment and low-resource environments where running a model client-side or on CPU matters more than raw speed. On TTS.ai it is offered on the free tier for English. Because the LLM-based pipeline is slow on long inputs, it is best used for shorter regular text rather than long-form cloning.
Oñeha'ãvéva: Edge deployment, browser-based TTS, low-resource environments
Ojehecha opavave OuteTTS ñe'ẽPeteĩ jehecha
- Desarrollador
- OuteAI
- Licencia
- Apache 2.0
- Ta'ãnga
- free
- Velocidad
- slow
- Clonación ñe'ẽnguéra rehe
- No
- Ñe'ẽ
- English
- Caracteres máx.
- 1000