How AI describes Bark

Bark is a transformer-based text-to-audio model by Suno that converts text into highly realistic multilingual speech and other audio, including music, background noise, and simple sound effects, as well as nonverbal cues like laughter or sighing. It provides pretrained checkpoints for inference and is intended for research use, with uncensored outputs and caveats about dual-use. The model can be run via Hugging Face Transformers pipelines or the original Bark library, and consists of three stages (text to semantic tokens, semantic to coarse tokens, and coarse to fine tokens) to produce mono 24 kHz audio, with available small and large checkpoints.