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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 Nodau · Cofrestru am 5,000 y genhedlaeth →
Cofrestru am gyfyngiad 5,000 nod

Amlapio' ch testun mewn tagiau SSML er mwyn cael rheoli cywir:

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

Tags y deall y model dewisiedig - cliciwch i daflu un i' ch testun lle mae' n digwydd:

Mae'r model yma yn darllen testun plaen, felly anwybyddir tagiau mewnlin. I ddelweddu teimlad yn seiliedig ar dagiau, newidiwch i ddelweddu mynegiant fel Orpheus neu Bark.

Diffinio ynganiad addasiedig (gair = ynganiad):

-12 +12
0.5x 2.0x
Am ddim gyda Piper, VITS, MeloTTS
Bydd eich sain a gynhyrchwyd yn ymddangos yma. Dewiswch ddull, rhowch destun, a chliciwch Creu.
Creuwyd Sain yn Llwyddiannus
0:00
Lawrlwytho Sain Lawrlwytho.srt Mae'r cyswllt yn darfod mewn 24 awr
Haen rhad: defnydd personol. Trwydded fasnachol o $5/mis
Gwneud hwn yn eich llais eich hun Clonio llais mewn 30 eiliad
Hoffwch TTS.ai? Meddwl am eich ffrindiau!

Am 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.

Gorau ar gyfer: Edge deployment, browser-based TTS, low-resource environments

Pori Popeth OuteTTS Saesneg

Yn syth

Datblygwr
OuteAI
Trwydded
Apache 2.0
o Fawrth
free
Cyflymder
slow
Clonio llais
Na
Iaith:
English
Uchafswm nodau
1000

OuteTTS Saesneg

Female 1 (Neutral)

English
Rhydd Female

OuteTTS TTS - Cwestiynau Cyffredin

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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