workflow-templates-broken-zap-2026-06-08/site/knowledge/models/chatterbox.md

Chatterbox

Chatterbox is a family of state-of-the-art open-source text-to-speech models developed by Resemble AI, featuring zero-shot voice cloning and emotion control.

Model Variants

Chatterbox Turbo

• 350M parameters, single-step mel decoding for low latency
• Paralinguistic tags for non-speech sounds ([laugh], [cough], [chuckle])
• English only, optimized for voice agents and production use

Chatterbox (Original)

• 500M parameter Llama backbone, English only
• CFG and exaggeration control for emotion intensity

Chatterbox Multilingual

• 500M parameters, 23 languages (Arabic, Chinese, French, German, Hindi, Japanese, Korean, Spanish, and more)
• Zero-shot voice cloning across languages

Key Features

• Zero-shot voice cloning from a few seconds of reference audio
• Emotion exaggeration control (first open-source model with this feature)
• Built-in PerTh neural watermarking for responsible AI
• Sub-200ms latency for real-time applications
• Trained on 500K hours of cleaned speech data
• MIT license (free for commercial use)
• Outperforms ElevenLabs in subjective evaluations

Hardware Requirements

• Minimum: NVIDIA GPU with CUDA support
• Turbo model requires less VRAM than original due to smaller architecture
• Runs on consumer GPUs (RTX 3060 and above)
• CPU inference possible but significantly slower

Common Use Cases

• Voice cloning for content creation
• AI voice agents and assistants
• Audiobook narration
• Game and media dialogue generation

Key Parameters

• exaggeration: Emotion intensity control (0.0 to 1.0, default 0.5)
• cfg_weight: Classifier-free guidance weight (0.0 to 1.0, default 0.5)
• audio_prompt_path: Path to reference audio clip for voice cloning
• language_id: Language code for multilingual model (e.g., "fr", "zh", "ja")