StyleTTS 2

StyleTTS 2 TTS

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

Skráðu þig inn fyrir 5.000 stafa takmörk

Wrap texta í SSML tags fyrir nákvæma stjórn:

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

Merki sem valið líkan skilur — smelltu til að sleppa einu í textann þinn þar sem það gerist:

Þetta líkan les venjulegan texta, þannig að innlínumerki eru hunsuð. Fyrir merki sem byggja á tilfinningum, skiptu yfir í tjáningarlíkan eins og Orpheus eða Bark.

Skilgreindu sérsniðna framburð (orð = framburð):

-12 +12
0.5x 2.0x
Frjáls með Piper, VITS, MeloTTS
Hljóðskráin þín birtist hér. Veldu líkan, sláðu inn texta og smelltu á Búa til.
Hljóð búið til
0:00
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Um 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.

Best fyrir: Studio-quality single-speaker synthesis, professional narration

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Í hnotskurn

Forritari
Columbia University
Leyfi
MIT
Tími
premium
Hraði
medium
Raddklóðun
Nei
Tungumál
English
Hámarksstafir
500

StyleTTS 2 raddir

Default

English
Premium Neutral

StyleTTS 2 TTS — Algengar spurningar

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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