Clibeanna a thuigeann an tsamhail roghnaithe — cliceáil chun ceann a scaoileadh isteach i do théacs nuair a tharlaíonn sé:
Léann an tsamhail seo gnáth- théacs, mar sin déantar neamhaird ar chlibeanna inlíne. Chun mothúchán clibbhunaithe a chruthú, athraigh go samhail léiritheach cosúil le Orpheus nó Bark.
Cues seachadta teanga nádúrtha. Onóracha ag Qwen3-TTS inniu; samhlacha sainráiteacha eile ag teacht go luath.
Ní thacaíonn an tsamhail seo le treoracha stíle — athraigh go samhail a dhéanann (m.sh. Qwen3-TTS).
Rialú ar an sainráiteacht (0 = neodrach, 1 = an- sainráiteach)
Meáchan treorach saor ó aicmitheoir (níos airde = níos mó leanúnach)
Déan cur síos ar an stíl gutha i dteanga nádúrtha (úsáideann Parlaimint é seo in ionad guthanna réamhshocraithe)
Formáid Dialóg Dia: Úsáid clibeanna < code > [S1] agus < code > [S2] chun cainteoirí éagsúla a mharcáil. Sampla: < code > [S1] Dia duit! [S2] Dia duit, cad atá ar siúl agat?
Is samhail gutha préimhe é seo, atá ar fáil ar aon phlean íoctha. Is féidir leat réamhamharc a dhéanamh ar a guthanna saor in aisce leis an gcnaipe seinn in aice leis an roghnóir gutha.
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.
Is Fearr le haghaidh: Edge deployment, browser-based TTS, low-resource environments
CC BY-NC-SA 4.0 (weights, non-commercial) + Llama 3.2 Community (base)
Úsáid phearsanta agus neamhthráchtála amháin
Tír
free
Luas
slow
Clónáil gutha
& Ná Sábháil
Teangacha
English
Carachtair Uasta
1000
OuteTTS guthanna
Female 1 (Neutral)
English
SaorFemaleÚsáid phearsanta agus neamhthráchtála amháin
OuteTTS TTS - Ceisteanna Coitianta
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.
Cuir isteach do r-phost chun labhairt a ghiniúint saor in aisce, nó cláraigh le haghaidh 15,000 carachtar bónais.
Níl aon phasfhocal ag teastáil — cuirfimid nasc chugat ar ríomhphost chun ceann a shocrú níos déanaí.
Teorainn Sraithe Saor Bainte Amach
Tá tú ag úsáid do 5,000 carachtair laethúil saor in aisce.Cruthaigh cuntas saor in aisce a fháil 15,000 carachtair bónas móide 10,000 carachtair saor in aisce gach mí.
