Parler TTS

Parler TTS TTS

Describe the voice you want in plain English and Parler generates speech matching that description.

Kulembetsa for 5,000 characters limit

Wrap wanu malemba mu SSML tags kwa kuwongolera moyenera:

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

Tags chosankhidwa chitsanzo amamvetsa - dinani kuti aphe mmodzi m'mawu anu pamene chimachitika:

Izi ndi njira yolemba malemba oyera, kotero ma tag ophatikizidwa amasiya kuganiziridwa. Kuti mupange ma tag ogwirizana ndi maganizo, gwiritsani ntchito njira yolemba malemba monga Orpheus kapena Bark.

Define custom pronunciations (word = pronunciation):

-12 +12
0.5x 2.0x
Free ndi Piper, VITS, MeloTTS
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Kukonda TTS.ai? udzauza anzanu!

Za Parler TTS

Parler TTS, developed by Hugging Face, replaces voice presets with natural-language control: instead of picking from a fixed list, you write a description such as "a warm female voice with a slight British accent, speaking slowly and clearly," and the model synthesizes speech to match. This makes it unusually flexible for creative work where you need a specific, custom voice character without recording or cloning anyone. It is an 880M-parameter transformer encoder-decoder trained on roughly 45,000 hours of speech, and it is released under the permissive Apache 2.0 license. Parler is English-focused and best suited to applications that benefit from on-demand, describable voice characteristics.

Best kwa: Creative applications where you need custom voice characteristics

Pezani zonse Parler TTS maganizo

Pa mphindi

Wopanga
Hugging Face
License
Apache 2.0
Mtundu
standard
Kuyenda
medium
Kusintha kwa mawu
Si
Zilankhulo
English
Max characters
500

Parler TTS maganizo

Default

English
Choyambirira Neutral

Parler TTS TTS — Mafunso Ofala

You describe it in natural language — gender, accent, pace, tone, and recording quality — and Parler generates speech matching the description. There are no preset voices to choose from.

Hugging Face. It is an 880M-parameter transformer encoder-decoder trained on around 45,000 hours of speech and released under Apache 2.0.

No. Parler generates a voice from a text description rather than from a reference recording. For cloning a specific voice, use a model like Chatterbox or GPT-SoVITS.
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