StyleTTS 2

StyleTTS 2 TTS

Reaches human-level single-speaker synthesis through style diffusion and adversarial training.

Cláraigh anois! le haghaidh teorainn 5,000 carachtar

Cuir do théacs i gclibeanna SSML le haghaidh rialú beacht:

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

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.

Sainmhínigh fuaimniú saincheaptha (focal = fuaimniú):

-12 +12
0.5x 2.0x
Saor in Aisce le Piper, VITS, MeloTTS
Taispeánfar an fhuaim a ghintear anseo. Roghnaigh samhail, iontráil téacs, agus cliceáil Giniúint.
D' éirigh le giniúint na fuaime
0:00
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Eolas Faoi StyleTTS 2

StyleTTS 2, developed at Columbia University, achieves human-level text-to-speech for single-speaker synthesis by combining style diffusion with adversarial training guided by large speech language models. Its diffusion-based style modeling captures the full natural variation of human speech — subtle shifts in rhythm, emphasis, and tone — so output can rival real recordings. It is widely regarded as one of the most natural-sounding open single-speaker models, which makes it a strong choice for studio-quality narration and professional voiceover where polish matters more than cloning or multilingual range. StyleTTS 2 is English-focused and released under the permissive MIT license.

Is Fearr le haghaidh: Studio-quality single-speaker synthesis, professional narration

Brabhsáil Uile StyleTTS 2 guthanna

Ag Sracfhéachaint

Forbróir
Columbia University
Ceadúnas
MIT
Tír
premium
Luas
medium
Clónáil gutha
& Ná Sábháil
Teangacha
English
Carachtair Uasta
500

StyleTTS 2 guthanna

Default

English
Préimh Neutral

StyleTTS 2 TTS - Ceisteanna Coitianta

It combines style diffusion with adversarial training using large speech language models. The diffusion-based style modeling captures the full range of human speech variation, producing output that can rival real recordings.

No. It is focused on producing the most natural single-speaker synthesis rather than cloning a specific voice. For cloning, use a model like Chatterbox or GPT-SoVITS.

Studio-quality single-speaker work — professional narration and voiceover — where naturalness and polish are the priority. It is English-focused and MIT-licensed.
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