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OuteTTS

OuteTTS TTS

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

0/500 znakovi · Prijavite se za 5.000 po generaciji →
Prijavite se za ograničenje od 5.000 znakova

Omotajte tekst u SSML oznake za preciznu kontrolu:

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

Oznake koje odabrani model razumije — kliknite da biste ih ubacili u tekst gdje se pojavljuju:

Ovaj model čita običan tekst, tako da se inline oznake ignoriraju. Za emocije zasnovane na oznakama, prebacite se na ekspresivni model poput Orpheusa ili Bark-a.

Definirajte vlastite izgovore (riječ = izgovor):

-12 +12
0.5x 2.0x
Besplatno sa Piper, VITS, MeloTTS
Ovdje će se pojaviti vaš generirani audio. Izaberite model, unesite tekst i kliknite na Generiraj.
Audio uspješno generisan
0:00
Preuzmi audio Preuzmi.srt Link istječe za 24h
Free tier: personal use. Komercijalna licenca od $5/mjesečno
Volite TTS.ai?

O meni 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 prvi pogled

Programer
OuteAI
Licenca
CC BY-NC-SA 4.0 (weights, non-commercial) + Llama 3.2 Community (base)
Samo za ličnu i nekomercijalnu upotrebu
Životinje
free
Brzina
slow
Kloniranje glasa
Ne, ne, ne.
Jezici
English
Maksimalan broj znakova
1000

OuteTTS glasovi

Female 1 (Neutral)

English
Slobodan Female Samo za ličnu i nekomercijalnu upotrebu

OuteTTS 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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