huggingface/parler-tts

Health v2 · maintenance only

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5586 stars · 588 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Parler-TTS is a lightweight text-to-speech library from Hugging Face that generates high-quality, natural-sounding speech controllable via text descriptions of speaker style. It includes both inference and training code, with fully open datasets, weights, and training pipeline.

Use cases

• generate speech from text with a described voice style
• train a custom text-to-speech model on my own data
• convert text to natural sounding audio in Python
• control gender, pitch, and speaking style of synthesized speech
• run fast TTS inference with flash attention on GPU
• build an audiobook narration generator

When to choose

• you need fully open-source TTS with permissive licensing
• you want text-prompt control over voice characteristics
• you plan to fine-tune or train your own TTS model
• you want lightweight dependencies and Hugging Face ecosystem integration

When to avoid

• you need zero-shot voice cloning from a short audio sample
• you need streaming real-time TTS for production voice assistants
• you want a plug-and-play GUI without writing code

Facets

library · maturity active

tts machine-learning llm-training speech-processing deep-learning artificial-intelligence python cross-platform text-to-speech huggingface open-source-models voice-cloning audio-generation gpu

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For agents

markdown · JSON · MCP: product_card(name="huggingface/parler-tts")