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OuteTTS

OuteTTS TTS

An LLM-based TTS that runs on CPU, GPU, or even in the browser via llama.cpp and Transformers.js.

0/500 aksara · 5000 kanggo saben generasi →
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
Love TTS.ai? Nyathet kanca-kancamu!

About OuteTTS

OuteTTS by OuteAI takes a language-model approach to speech: it extends an LLM with text-to-speech capability while keeping the original architecture intact, so it can run through standard LLM tooling. That gives it unusually broad backend support — llama.cpp on CPU or GPU, Hugging Face Transformers, ExLlamaV2, VLLM, and even in-browser inference via Transformers.js. It is a natural fit for edge deployment and low-resource environments where running a model client-side or on CPU matters more than raw speed. On TTS.ai it is offered on the free tier for English. Because the LLM-based pipeline is slow on long inputs, it is best used for shorter regular text rather than long-form cloning.

Paling apik kanggo: Edge deployment, browser-based TTS, low-resource environments

Nglayar kabeh OuteTTS suara

Ing cetha

Pangembang
OuteAI
Lisensi
Apache 2.0
Tingkat
free
Kecepatan
slow
Kloning suara
Ora
Basa
English
Karakter paling akeh
1000

OuteTTS suara

Female 1 (Neutral)

English
Bebas Female

OuteTTS TTS — FAQ

Across many backends — llama.cpp (CPU or GPU), Hugging Face Transformers, ExLlamaV2, VLLM, and even directly in the browser through Transformers.js — because it preserves the underlying LLM architecture.

Its LLM-based design runs efficiently on CPU and in the browser, so it can operate client-side or on modest hardware without a dedicated GPU.

It works best on shorter inputs. The LLM-based pipeline is slow on long passages, so it is offered for regular short-to-medium TTS rather than long-form generation.
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