StyleTTS 2

StyleTTS 2 TTS

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

Ojejapo 5000 caracter rehegua límite

Ojehaijey ñe'ẽnguéra etiquetas SSML-pe peteĩ control hekopete g̃uarã:

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

Etiquetas ohechakuaáva modelo ojeporavóva - tesãirã peteĩ peteĩva ñe'ẽnguérape, oĩhápe:

Ko modelo ohai texto ndahasyivéva, upévare umi etiqueta oĩva línea ryepýpe ndojehechakuaái. Umi emoción oñemopyendáva etiqueta-pe g̃uarã, oñemoambue peteĩ modelo expresivo-pe taha'e Orfeo térã Bark.

Oñemohenda ñe'ẽnguéra ojehechapyréva (tembiapo = ñe'ẽnguéra):

-12 +12
0.5x 2.0x
Libre Piper, VITS, MeloTTS ndive
Audio-kuéra oguenohẽva ojekuaauka ko'ápe. Oñeporavo peteĩ modelo, omoĩnge ñe'ẽ ha ohesa'ỹijo Generar.
Audio oñemoheñói porã
0:00
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Nivel libre: jeiporu personal. Licencia comercial $5/ha'e rupi
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Mba'épa 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.

Oñeha'ãvéva: Studio-quality single-speaker synthesis, professional narration

Ojehecha opavave StyleTTS 2 ñe'ẽ

Peteĩ jehecha

Desarrollador
Columbia University
Licencia
MIT
Ta'ãnga
premium
Velocidad
medium
Clonación ñe'ẽnguéra rehe
No
Ñe'ẽ
English
Caracteres máx.
500

StyleTTS 2 ñe'ẽ

Default

English
Premium Neutral

StyleTTS 2 Pregunta ojehechavéva

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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