StyleTTS 2

StyleTTS 2 TTS

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

Ndaftar for 5,000 characters limit

Nglapisi teks ing tag SSML kanggo kontrol sing tepat:

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

Tag kang dipahami model kang dipilih — klik kanggo ngethok siji menyang teks sampeyan ing ngendi iku kedadeyan:

Model ieu maca teks biasa, jadi tag inline diabaikan. Pikeun emosi dumasar tag, ganti ka model ekspresif kayaning Orpheus atawa Bark.

Nyathet pangucapan standar (kata = pangucapan):

-12 +12
0.5x 2.0x
Bebas karo Piper, VITS, MeloTTS
Audio anu dihasilkeun bakal muncul di dieu. Pilih model, ketok teks, sarta ketok Janji.
Audio berhasil diciptakan
0:00
Muat turun audio Muat turun.srt Link expires in 24h
Kacamatan iki kalebu: Kacamatan Semarang. Lisénsi komersial saka $ 5 / mo
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About 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.

Paling apik kanggo: Studio-quality single-speaker synthesis, professional narration

Nglayar kabeh StyleTTS 2 suara

Ing cetha

Pangembang
Columbia University
Lisensi
MIT
Tingkat
premium
Kecepatan
medium
Kloning suara
Ora
Basa
English
Karakter paling akeh
500

StyleTTS 2 suara

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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