Bark is a text-prompted generative audio model that produces realistic, multilingual speech, music, and sound effects. It's designed for researchers and power users seeking a flexible audio generation tool beyond traditional text-to-speech. Bark offers creative control and can generate non-speech sounds like laughter and sighs, with a focus on realistic voice and prosody.

How It Works

Bark is a transformer-based, fully generative text-to-audio model, similar to AudioLM and Vall-E. It uses a quantized audio representation from EnCodec. Unlike conventional TTS, Bark converts text directly to audio without intermediate phonemes, enabling generalization to music, sound effects, and non-speech sounds. It supports voice presets for tone, pitch, and emotion matching, but not custom voice cloning.

Quick Start & Requirements

• Install via pip: pip install git+https://github.com/suno-ai/bark.git or clone and install locally.
• Requires PyTorch 2.0+, CUDA 11.7/12.0 for GPU acceleration.
• Full model requires ~12GB VRAM; smaller models available for <4GB VRAM using SUNO_USE_SMALL_MODELS=True.
• Official Docs: https://suno-ai.notion.site/Bark-models-and-how-to-use-them-f5101f7760014427877312006307230a
• Hugging Face Integration: https://huggingface.co/docs/transformers/main/en/model_doc/bark

Highlighted Details

• Supports 100+ speaker presets across multiple languages.
• Can generate music, background noise, and sound effects alongside speech.
• Offers automatic language detection and accent generation for code-switched text.
• Long-form generation capabilities are documented in provided notebooks.

Maintenance & Community

• Active community on Discord: https://discord.gg/J2B2vsjKuE
• Model playground early access sign-up available.

Licensing & Compatibility

• Licensed under the MIT License, permitting commercial use.

Limitations & Caveats

Bark is a research model and may deviate unexpectedly from prompts, producing higher variance outputs than traditional TTS. Generations are typically limited to ~13-14 seconds due to its GPT-style architecture. Audio quality can vary, sometimes resembling older phone calls.