StyleTTS 2

StyleTTS 2 TTS

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

Upišite se za 5000 ograničenja znakova

Umotaj svoj tekst u SSML oznake za preciznu kontrolu:

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

Oznake odabrani model razumije — kliknite da bacite jedan u vaš tekst gdje se to događa:

Ovaj model čita običan tekst, tako da inline oznake se zanemaruju. Za tag-based emocije, prebaci na ekspresivni model kao što su Orfeus ili Bark.

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-12 +12
0.5x 2.0x
Besplatno s Piper, VITS, Melotts
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O 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.

Najbolje za: Studio-quality single-speaker synthesis, professional narration

Pregledaj sve StyleTTS 2 glasovi

Na jedan pogled

Programer
Columbia University
Dozvola
MIT
Nivo
premium
Brzina
medium
Kloniranje glasa
Ne.
Jezici
English
Maks. znakova
500

StyleTTS 2 glasovi

Default

English
Premium Neutral

StyleTTS 2 TTS – FAQ

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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