OuteTTS

OuteTTS TTS

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

Misoratra anarana fetra 5000 marika

Ampidiro anatin'ny tag SSML ny lahabolana mba hahazoana fifehezana mazava tsara:

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

Tag fantatry ny modely voafaritra — tsindrio mba hametrahana iray ao anatin'ny lahatsoratrao izay misy azy:

Mamakiana lahabolana tsotra io modely io, ka tsy raharahaina ny tag anatin'ny andalana. Raha mila fihetseham-po mifototra amin'ny tag ianao, dia miova ho modely maneho fihetseham-po toy ny Orpheus na Bark.

Mamaritra ny fanononana safidy (teny = fanononana):

-12 +12
0.5x 2.0x
Malalaka miaraka amin'ny Piper, VITS, MeloTTS
Hiseho eto ny feo namoronanao. Misafidiana modely iray, soraty ny lahabolana, dia tsindrio ny Mamorona.
Namorona feo tsara
0:00
Handefa feo Hidina.srt Tapitra ao anatin'ny 24 ora ity rohy ity
Ny faritr'ora dia GMT+1. : Tranonkala ofisialy Lisansa ara-barotra manomboka amin'ny $5/volana
Tianao ve ny TTS.ai? Lazao amin'ny namanao!

Mombamomba 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.

Tsara indrindra ho an'ny: Edge deployment, browser-based TTS, low-resource environments

Jereo izy rehetra OuteTTS feo

Amin'ny fijery fohy

Mpamorona
OuteAI
Lisansa
Apache 2.0
Taona
free
Hafainganan'ny fanovana
slow
Fandraisana feo
Tsy misy
Teny
English
Marika betsaka indrindra
1000

OuteTTS feo

Female 1 (Neutral)

English
Free Female

OuteTTS TTS - Fanontaniana matetika

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.
← Ny feo rehetra