Kani TTS 2

Kani TTS 2 TTS

An ultra-lightweight 400M English model that runs in just 3GB of VRAM at a 0.2 real-time factor.

Daftar untuk batas 5,000 karakter

Bungkus teks Anda dalam tag SSML untuk kendali yang tepat:

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

Tag yang dipilih mengerti klik °C untuk memasukkan satu ke dalam teks Anda di mana hal itu terjadi:

Model ini membaca teks biasa, sehingga tag inline diabaikan. Untuk tag berbasis emosi, beralih ke model ekspresif seperti Orpheus atau Bark.

Definisikan pengucapan ubahan (kata = pelafalan):

-12 +12
0.5x 2.0x
Free with Piper, VITS, Melotts
Audio yang Anda buat akan muncul di sini. Pilih model, masukkan teks, dan klik Generate.
Hasil Audio Berhasil
0:00
Unduh Audio Unduh.srt Sambungan berakhir dalam 24 jam
Tingkatan bebas: penggunaan pribadi. Ijin komersial dari $5/mo
Buatlah ini suara Anda sendiri Kloning suara dalam 30 detik
Beritahu teman-temanmu!

Tentang Kani TTS 2

Kani-TTS-2 by NineNineSix is an ultra-lightweight 400M-parameter text-to-speech model built on a Liquid AI LFM2 backbone with NVIDIA's NanoCodec. It runs in just 3GB of VRAM and generates roughly ten seconds of speech in about two seconds on an A100 — a real-time factor near 0.2. The current public release ships an English-only checkpoint and, unlike its predecessor, does not expose the speaker-embedding hook needed for voice cloning. Its strength is fast, low-cost English generation on modest hardware, which makes it a good fit for quick previews and high-volume English narration. It is released under Apache 2.0 and offered on the free tier.

Terbaik untuk: Fast English generation on low-VRAM hardware, quick previews

Jelajahi semua Kani TTS 2 suara

Pada sekilas

Pengembang
NineNineSix
Lisensi
Apache 2.0
Tier
free
Kecepatan
fast
Penklonan Suara
Tidak
Bahasa
English
Karakter maksimal
1000

Kani TTS 2 suara

Default

English
Standar Neutral

Kani TTS 2 TTS °F FAQ

It runs in just 3GB of VRAM and produces about ten seconds of speech in roughly two seconds on an A100 — a real-time factor near 0.2 — thanks to its 400M-parameter LFM2 backbone and NanoCodec.

No. The current v2 release removed the public speaker-embedding hook, so cloning is not available. For cloning, use Chatterbox, IndexTTS-2, or GPT-SoVITS.

English only. The public release ships a single English checkpoint; for non-English speech, use a model like Kokoro or MeloTTS.
← Semua suara