
openvino-plugins-ai-audacity
A set of AI-enabled effects, generators, and analyzers for Audacity®.
Stars: 885

OpenVINO™ AI Plugins for Audacity* are a set of AI-enabled effects, generators, and analyzers for Audacity®. These AI features run 100% locally on your PC -- no internet connection necessary! OpenVINO™ is used to run AI models on supported accelerators found on the user's system such as CPU, GPU, and NPU. * **Music Separation**: Separate a mono or stereo track into individual stems -- Drums, Bass, Vocals, & Other Instruments. * **Noise Suppression**: Removes background noise from an audio sample. * **Music Generation & Continuation**: Uses MusicGen LLM to generate snippets of music, or to generate a continuation of an existing snippet of music. * **Whisper Transcription**: Uses whisper.cpp to generate a label track containing the transcription or translation for a given selection of spoken audio or vocals.
README:
A set of AI-enabled effects, generators, and analyzers for Audacity®. These AI features run 100% locally on your PC 💻 -- no internet connection necessary! OpenVINO™ is used to run AI models on supported accelerators found on the user's system such as CPU, GPU, and NPU.
- Music Separation🎵 -- Separate a mono or stereo track into individual stems -- Drums, Bass, Vocals, & Other Instruments.
- Noise Suppression🧹 -- Removes background noise from an audio sample.
- Music Generation & Continuation🎶 -- Uses MusicGen LLM to generate snippets of music, or to generate a continuation of an existing snippet of music.
- Whisper Transcription🎤 -- Uses whisper.cpp to generate a label track containing the transcription or translation for a given selection of spoken audio or vocals.
Go here to find installation packages & instructions for the latest Windows release.
We welcome you to submit an issue here for
- Questions
- Bug Reports
- Feature Requests
- Feedback of any kind -- how can we improve this project?
Your contributions are welcome and valued, no matter how big or small. Feel free to submit a pull-request!
- Audacity® development team & Muse Group-- Thank you for your support!
- Audacity® GitHub -- https://github.com/audacity/audacity
- Whisper transcription & translation analyzer uses whisper.cpp (with OpenVINO™ backend): https://github.com/ggerganov/whisper.cpp
- Music Generation & Continuation use MusicGen model, from Meta.
- We currently have support for MusicGen-Small, and MusicGen-Small-Stereo
- The txt-to-music pipelines were ported from python to C++, referencing logic from the Hugging Face transformers project: https://github.com/huggingface/transformers
- Music Separation effect uses Meta's Demucs v4 model (https://github.com/facebookresearch/demucs), which has been ported to work with OpenVINO™
- Noise Suppression:
- noise-suppression-denseunet-ll: from OpenVINO™'s Open Model Zoo: https://github.com/openvinotoolkit/open_model_zoo
- DeepFilterNet2 & DeepFilterNet3:
- Ported the models & pipeline from here: https://github.com/Rikorose/DeepFilterNet
- We also made use of @grazder's fork / branch (https://github.com/grazder/DeepFilterNet/tree/torchDF-changes) to better understand the Rust implementation, and so we also based some of our C++ implementation on
torch_df_offline.py
found here. - Citations:
@inproceedings{schroeter2022deepfilternet2, title = {{DeepFilterNet2}: Towards Real-Time Speech Enhancement on Embedded Devices for Full-Band Audio}, author = {Schröter, Hendrik and Escalante-B., Alberto N. and Rosenkranz, Tobias and Maier, Andreas}, booktitle={17th International Workshop on Acoustic Signal Enhancement (IWAENC 2022)}, year = {2022}, } @inproceedings{schroeter2023deepfilternet3, title = {{DeepFilterNet}: Perceptually Motivated Real-Time Speech Enhancement}, author = {Schröter, Hendrik and Rosenkranz, Tobias and Escalante-B., Alberto N. and Maier, Andreas}, booktitle={INTERSPEECH}, year = {2023}, }
- OpenVINO™ Notebooks -- We have learned a lot from this awesome set of python notebooks, and are still using it to learn latest / best practices for implementing AI pipelines using OpenVINO™!
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