OuteTTS

OuteTTS TTS

An LLM-based TTS that runs on CPU, GPU, or even in the browser via llama.cpp and Transformers.js.

Teken op vir 5 000 karakterbeperking

Oorvloei jou teks in SSML etiket vir presiese beheer:

<speak><prosody rate="slow">Slow speech</prosody></speak>

Merk die gekose model verstaan ooit die woord ooit om een in jou teks te laat val waar dit gebeur:

Hierdie model lees gewone teks, so inlyn etiket word geignoreer. Vir etiket-gebaseerde emosie, wissel na 'n uitdrukkingende model soos Orpheus of Bark.

Definieer pasmaak uitspraak (woord = uitspraak):

-12 +12
0.5x 2.0x
Vry met Pyper, VITS, MiloTTS
Jou gegenereer oudio sal hier verskyn. Kies 'n model, invoer teks, en kliek Genereer.
Klank Genereer suksesvol
0:00
Aflaai klaar gemaak Aflaai klaar gemaak Skakel verstrek in 24h
Vryvlak: persoonlike gebruik. Kommonsielisensie van R5/m
Liefde TTS.ai, vertel jou vriende!

Aangaande 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.

Beste vir: Edge deployment, browser-based TTS, low-resource environments

Blaai deur almal OuteTTS stemme

Met'n blik

Ontwikkelingvloeistof is minDeveloper
OuteAI
Lisensie
Apache 2.0
Tier
free
Spoed
slow
Stem kloning
Nee
Tale
English
Voeg- agteraan- by Taal
1000

OuteTTS stemme

Female 1 (Neutral)

English
Beskikbaar Female

OuteTTS TTS ← FAQ

Across many backends — llama.cpp (CPU or GPU), Hugging Face Transformers, ExLlamaV2, VLLM, and even directly in the browser through Transformers.js — because it preserves the underlying LLM architecture.

Its LLM-based design runs efficiently on CPU and in the browser, so it can operate client-side or on modest hardware without a dedicated GPU.

It works best on shorter inputs. The LLM-based pipeline is slow on long passages, so it is offered for regular short-to-medium TTS rather than long-form generation.
← Alle stemme