StyleTTS 2

StyleTTS 2 TTS

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

Vpišite se. za 5000 mejnih vrednosti znakov

Za natančen nadzor zavijte svoje besedilo v oznake SSML:

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

Oznake izbranega modela razume – kliknite, da spustite enega v svoje besedilo, kjer se zgodi:

Ta model bere navadno besedilo, zato se v vrstici ignorirajo. Za čustva, ki temeljijo na tag, preklopite na izražen model, kot je Orfeus ali Bark.

Opredelitev posebnih izgovorov (beseda = izgovor):

-12 +12
0.5x 2.0x
Brez Piper, VITS, Melotts
Tukaj se bo pojavil vaš ustvarjeni zvok. Izberite model, vnesite besedilo in kliknite Generiraj.
Uspešno ustvarjen zvok
0:00
Prenesi zvok Prenesi.rt Povezava poteče čez 24h
Brezplačna stopnja: osebna uporaba. Trgovska licenca od 5 $/mo
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O projektu 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.

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

Brskaj vse StyleTTS 2 glasovi

Na pogled

Razvijalec
Columbia University
Licenca
MIT
Stopnja
premium
Hitrost
medium
kloniranje glasu
Ne
Jeziki
English
Največ znakov
500

StyleTTS 2 glasovi

Default

English
Premium Neutral

StyleTTS 2 TTS – Pogosta vprašanja

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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