Example Python File
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, welcome to LinuxLinks. [laughs]
We hope you love our content. ♪
"""
audio_array = generate_audio(text_prompt)
# save audio to disk
write_wav("bark-LinuxLinks.wav", SAMPLE_RATE, audio_array)
# play text in notebook
Audio(audio_array, rate=SAMPLE_RATE)
Pages in this article:
Page 1 – Introduction and Installation
Page 2 – In Operation and Summary
Page 3 – Example Python File
Related Software
| Speech Tools | |
|---|---|
| Piper | Fast, local neural text to speech system |
| Tortoise | Multi-voice text-to-speech system trained with an emphasis on quality |
| Coqui TTS | Offers pretrained models in more than 1,100 different languages |
| Bark | Transformer-based text-to-audio model. |
| Dia | 1.6B parameter text to speech model |
| Festival | General multi-lingual speech synthesis system |
| PraatSpeechAnalyser | Software for speech analysis and synthesis |
| Speech Note | Speech to Text, Text to Speech and Machine Translation |
| Mimic 3 | Lightweight Text to Speech engine |
| OrcaScreenReader | Scriptable screen reader |
| MeloTTS | High-quality multi-lingual text-to-speech library |
| Parler-TTS | Lightweight text-to-speech (TTS) model |
| Flite | Small, fast run time text to speech synthesis engine |
| RHVoice | Gives the visually impaired a synthesis voice with their screen reader |
| eSpeak NG | Continuation of the eSpeak project |
| eSpeak | Speech synthesizer using a formant synthesis method |
| Orpheus-TTS-FastAPI | High-performance self-hosted text-to-speech server |
| Gespeaker | GTK-based frontend for eSpeak |
| VoiceGen | Simple text-to-speech application |
| Glate | Google Translator and Text To Speech Service |
Read our verdict in the software roundup.
 Explore our comprehensive directory of recommended free and open source software. Our carefully curated collection spans every major software category.This directory is part of our ongoing series of informative articles for Linux enthusiasts. It features hundreds of detailed reviews, along with open source alternatives to proprietary solutions from major corporations such as Google, Microsoft, Apple, Adobe, IBM, Cisco, Oracle, and Autodesk. You’ll also find interesting projects to try, hardware coverage, free programming books and tutorials, and much more. Discovered a useful open source Linux program that we haven’t covered yet? Let us know by completing this form. |
Never heard of Bark before. It looks kinda interesting. I’ll give it a whirl under Ubuntu.
I’m using Debian so I should be able to get it working.
do what?
Can you run Bark without a dedicated graphics card? I’ve got a 5th generation Intel machine with 8GB of RAM.
We don’t recommend using Bark without a dedicated GPU, but it’s definitely possible to run it without one.
You’ll get a warning
“No GPU being used. Careful, inference might be very slow!”
And that’s definitely the case. A 5 second clip took over a minute to be generated on an Intel i5-10400 machine.
Even with an i9-13900K, processing is slow. A dedicated graphics card is a must for these machine learning apps.