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Bark

Transformer-based text-to-audio model that also laughs, sighs, and sings

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About

Bark is Suno's open-source transformer-based text-to-audio model. Unlike conventional TTS, it generates audio directly from text prompts with no phoneme intermediate — so the same prompt language controls speech, music, background noise, sound effects, and nonverbal sounds like [laughs], [sighs], [gasps], hesitations (...), emphasis via CAPS, and ♪ sung lyrics ♪. It is multilingual, ships large and small checkpoints (both on Hugging Face), is available in Transformers from 4.31.0, and comes with a voice prompt library and long-form generation notebooks. MIT-licensed since May 2023 with checkpoints explicitly available for commercial use. Suno flags it as research-grade: being fully generative, it can deviate from prompts unexpectedly.

What it can do

  • Multilingual text-to-speech from plain-text prompts (no phonemes needed)
  • Non-speech audio: music, background noise, simple sound effects
  • Nonverbal sounds: [laughs], [sighs], [gasps], [clears throat], hesitations, crying
  • Prompt tricks: ♪ for singing, CAPS for emphasis, [MAN]/[WOMAN] speaker bias
  • Voice consistency via history_prompt / voice prompt library
  • bark-small checkpoint for low-VRAM and CPU use
  • Long-form generation notebooks; Transformers (>=4.31.0) support
  • MIT checkpoints, explicitly available for commercial use

Setup

  1. Install from git (verified from README — do NOT pip install bark, that is an unrelated package):

```bash

pip install git+https://github.com/suno-ai/bark.git

```

or git clone https://github.com/suno-ai/bark && cd bark && pip install .

  1. Generate audio:

```python

from bark import SAMPLE_RATE, generate_audio, preload_models

preload_models() # downloads checkpoints on first run

audio_array = generate_audio("Hello, my name is Suno. [laughs]")

```

  1. Use a voice prompt for consistency: generate_audio(text, history_prompt="v2/en_speaker_6") — browse the voice prompt library linked in the README.
  2. Alternatively use the Transformers integration (transformers>=4.31.0) or the Hugging Face Space demo.

Prerequisites

Python with PyTorch. GPU recommended for practical speed (works on CPU, much slower; small checkpoint helps low-VRAM GPUs <4GB). scipy for WAV writing. Checkpoints download automatically on first `preload_models()`.

Use cases

ttsaudiomediavoice-cloning

Works with

Claude CodeCodexCursorAny agent (.md)Generic API

Trust score — 7/10

/10 trustVerified

Scored 7/10 (verified tier, metrics-v1). Evidence: 39,264 GitHub stars (log-scaled vs catalog peers); last push 785d ago; 0 releases/12mo; 269 open issues. Manual review: repo FROZEN since Aug 2024; fully generative outputs can deviate (Suno disclaimer); voice cloning deliberately restricted; PyPI `bark` is UNRELATED package. License: MIT (checkpoints commercial-use OK).

★ 39,264 GitHub stars

How the trust score is built

Full methodology →
Adoption · stars/downloads, log-scaled vs peers
8.6/10
Maintenance · recency, releases, issue load
3.6/10
Openness · license + docs
10.0/10
Manual review · sanity read + red-flag check
8.0/10
  • · 39,264 GitHub stars (log-scaled vs catalog peers)
  • · last push 785d ago; 0 releases/12mo; 269 open issues
  • · manual review: repo FROZEN since Aug 2024; fully generative outputs can deviate (Suno disclaimer); voice cloning deliberately restricted; PyPI `bark` is UNRELATED package

Sources

Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.