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# 🐶 Bark
Bark is a multi-lingual TTS model created by [Suno-AI](https://www.suno.ai/). It can generate conversational speech as well as music and sound effects.
It is architecturally very similar to Google's [AudioLM](https://arxiv.org/abs/2209.03143). For more information, please refer to the [Suno-AI's repo](https://github.com/suno-ai/bark).
## Acknowledgements
- 👑[Suno-AI](https://www.suno.ai/) for training and open-sourcing this model.
- 👑[gitmylo](https://github.com/gitmylo) for finding [the solution](https://github.com/gitmylo/bark-voice-cloning-HuBERT-quantizer/) to the semantic token generation for voice clones and finetunes.
- 👑[serp-ai](https://github.com/serp-ai/bark-with-voice-clone) for controlled voice cloning.
## Example Use
```python
text = "Hello, my name is Manmay , how are you?"
from TTS.tts.configs.bark_config import BarkConfig
from TTS.tts.models.bark import Bark
config = BarkConfig()
model = Bark.init_from_config(config)
model.load_checkpoint(config, checkpoint_dir="path/to/model/dir/", eval=True)
# with random speaker
output_dict = model.synthesize(text, config, speaker_id="random", voice_dirs=None)
# cloning a speaker.
# It assumes that you have a speaker file in `bark_voices/speaker_n/speaker.wav` or `bark_voices/speaker_n/speaker.npz`
output_dict = model.synthesize(text, config, speaker_id="ljspeech", voice_dirs="bark_voices/")
```
Using 🐸TTS API:
```python
from TTS.api import TTS
# Load the model to GPU
# Bark is really slow on CPU, so we recommend using GPU.
tts = TTS("tts_models/multilingual/multi-dataset/bark", gpu=True)
# Cloning a new speaker
# This expects to find a mp3 or wav file like `bark_voices/new_speaker/speaker.wav`
# It computes the cloning values and stores in `bark_voices/new_speaker/speaker.npz`
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
file_path="output.wav",
voice_dir="bark_voices/",
speaker="ljspeech")
# When you run it again it uses the stored values to generate the voice.
tts.tts_to_file(text="Hello, my name is Manmay , how are you?",
file_path="output.wav",
voice_dir="bark_voices/",
speaker="ljspeech")
# random speaker
tts = TTS("tts_models/multilingual/multi-dataset/bark", gpu=True)
tts.tts_to_file("hello world", file_path="out.wav")
```
Using 🐸TTS Command line:
```console
# cloning the `ljspeech` voice
tts --model_name tts_models/multilingual/multi-dataset/bark \
--text "This is an example." \
--out_path "output.wav" \
--voice_dir bark_voices/ \
--speaker_idx "ljspeech" \
--progress_bar True
# Random voice generation
tts --model_name tts_models/multilingual/multi-dataset/bark \
--text "This is an example." \
--out_path "output.wav" \
--progress_bar True
```
## Important resources & papers
- Original Repo: https://github.com/suno-ai/bark
- Cloning implementation: https://github.com/serp-ai/bark-with-voice-clone
- AudioLM: https://arxiv.org/abs/2209.03143
## BarkConfig
```{eval-rst}
.. autoclass:: TTS.tts.configs.bark_config.BarkConfig
:members:
```
## Bark Model
```{eval-rst}
.. autoclass:: TTS.tts.models.bark.Bark
:members:
```
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