OuteTTS

OuteTTS TTS

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

Upišite se za 5000 ograničenja znakova

Umotaj svoj tekst u SSML oznake za preciznu kontrolu:

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

Oznake odabrani model razumije — kliknite da bacite jedan u vaš tekst gdje se to događa:

Ovaj model čita običan tekst, tako da inline oznake se zanemaruju. Za tag-based emocije, prebaci na ekspresivni model kao što su Orfeus ili Bark.

Definiši vlastite izgovore (riječ = izgovor):

-12 +12
0.5x 2.0x
Besplatno s Piper, VITS, Melotts
Ovdje će se pojaviti vaš generirani zvuk. Odaberite model, unesite tekst i kliknite Generirati.
Zvučni generisan uspješno
0:00
Preuzmi zvuk Preuzmite.rt Veza isteče za 24 sata
Besplatna uporaba: osobna upotreba. Komercijalna licenca od $5/mo
Reci svojim prijateljima!

O 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.

Najbolje za: Edge deployment, browser-based TTS, low-resource environments

Pregledaj sve OuteTTS glasovi

Na jedan pogled

Programer
OuteAI
Dozvola
Apache 2.0
Nivo
free
Brzina
slow
Kloniranje glasa
Ne.
Jezici
English
Maks. znakova
1000

OuteTTS glasovi

Female 1 (Neutral)

English
Slobodno 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.
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