Introduction to Bark
Bark, developed by Suno, is a remarkable transformer-based text-to-audio model that has been making waves in the world of AI. It stands out for its ability to generate not only highly realistic, multilingual speech but also other types of audio such as music, background noise, and simple sound effects. Additionally, it can produce nonverbal communications like laughing, sighing, and crying.
Core Features
One of the key features of Bark is its multilingual support. It can handle various languages out-of-the-box and automatically determines the language from the input text. For instance, when given code-switched text, it will attempt to use the native accent for the respective languages. While English quality is currently quite good, the performance in other languages is expected to improve further with scaling.
Another notable aspect is its support for 100+ speaker presets across different languages. Users can browse the library of these presets to find a voice that suits their needs. Although it doesn't currently support custom voice cloning, it does a great job of matching the tone, pitch, emotion, and prosody of a given preset.
Bark also has the ability to generate all types of audio. It doesn't really distinguish between speech and music in principle. Sometimes it might choose to generate text as music, but this can be guided by adding music notes around the lyrics.
Basic Usage
Using Bark in Python is relatively straightforward. First, you need to download and load all the models using the preload_models() function. Then, you can generate audio from text by providing a text prompt. For example:
from bark import SAMPLE_RATE, generate_audio, preload_models
from scipy.io.wavfile import write as write_wav
from IPython.display import Audio
# download and load all models
preload_models()
# generate audio from text
text_prompt = "Hello, my name is Suno. And, uh — and I like pizza. [laughs] But I also have other interests such as playing tic tac toe."
audio_array = generate_audio(text_prompt)
# save audio to disk
write_wav("bark_generation.wav", SAMPLE_RATE, audio_array)
# play text in notebook
Audio(audio_array, rate=SAMPLE_RATE)
It's also available in the 🤗 Transformers library from version 4.31.0 onwards, which requires minimal dependencies and additional packages. This allows for easier integration into different projects.
In comparison to some existing text-to-speech models, Bark is a fully generative text-to-audio model. It doesn't follow the traditional TTS model approach where the input text prompt is first converted to phonemes and then to audio. Instead, it directly converts the text prompt to audio, enabling it to generalize to arbitrary instructions beyond speech, like music lyrics or sound effects.
Overall, Bark offers a unique and powerful tool for those looking to create a wide variety of audio content with the help of AI.
