StyleTTS 2

StyleTTS 2 TTS

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

Daftar masuk had 5,000 aksara

Lilitkan teks anda dalam tag SSML untuk kawalan tepat:

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

Tag model dipilih memahami - klik untuk jatuhkan satu ke dalam teks anda di mana ia berlaku:

Model ini membaca teks biasa, jadi tag dalam baris diabaikan. Untuk emosi berdasar tag, beralih ke model ekspresif seperti Orpheus atau Bark.

Tetapkan sebutan tersendiri (perkataan = sebutan):

-12 +12
0.5x 2.0x
Bebas dengan Piper, VITS, MeloTTS
Audio yang dijana akan muncul di sini. Pilih model, masukkan teks, dan klik Janakan.
Audio Dijana Dengan Berjaya
0:00
Muat turun Audio Muat turun.srt Pautan luput dalam 24 jam
Tahap percuma: penggunaan peribadi. Lesen Komersial dari $5/mo
Cinta TTS.ai? Beritahu kawan-kawan anda!

Tentang 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.

Terbaik untuk: Studio-quality single-speaker synthesis, professional narration

Layari semua StyleTTS 2 suara

Dengan sekejap mata

Pemaju
Columbia University
Lesen
MIT
Tajuk
premium
Kelajuan
medium
Klon suara
Tidak
Bahasa
English
Aksara maksimum
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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