Umbhalo usuka kumazwi Ama-AI Agents Umculo Ukukhuluma kuMbhalo Ukulungiswa kwezwi Uhlelo lwezwi Imakethe Okuningi
Umbiko wephutha / Umbuzo wezici
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 amaphawu · Ubhalise nge-5,000 ngenkulumo →
Bhala for 5,000 characters limit

Ukufaka umbhalo wakho kumathegi we-SSML ukulawula okucacile:

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

Amathegi amamodeli akhethiwe aqonda - chofoza ukuwasusa kusihloko sakho lapho kwenzeka khona:

Le modeli ifunda umbhalo ojwayelekile, ngakho amathegi e-inline akhohlwa. Ukwenza umbono osekelwe kumathegi, shintsha kwimodeli ebonisa umbono njenge-Orpheus noma i-Bark.

Chaza ukuchaza okujwayelekile (igama = ukuchaza):

-12 +12
0.5x 2.0x
Imahhala ne-Piper, VITS, MeloTTS
Umsindo wakho okhiqizwe uzovela lapha. Khetha imodeli, ngenisa umbhalo, bese uchofoza Ukukhiqiza.
Umsindo wakhiwa ngokuphumelelayo
0:00
Layisha phezulu umsindo Layisha phezulu.srt Isixhumanisi siphele ngehora le-24
Isikhashana esimahhala: ukusetshenziswa komuntu siqu. Ilayisense yebhizinisi kusuka ku-$5/mo
Yenza lokhu kube umsindo wakho Uhlu lwezinhlamvu
Uthanda i-TTS.ai? Ncoma abangane bakho!

Ngo 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.

Okungcono kakhulu: Edge deployment, browser-based TTS, low-resource environments

Khangela konke OuteTTS izizwi

Ngombono ocacile

Umthuthukisi
OuteAI
Ilayisense
Apache 2.0
I-Tiger
free
Isivinini
slow
Ukuklona umsindo
Akukho
Izilimi
English
Amaphawu aphezulu
1000

OuteTTS izizwi

Female 1 (Neutral)

English
Ikhululekile Female

OuteTTS Imibuzo ebuzwa kaningi

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.
← Zonke izizwi