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https://github.com/GareBear99/awesome-python-audio-science

A curated, public-facing list of Python audio science, scientific audio research, music information retrieval, DSP, machine learning audio, datasets, notebooks, and creator-audio tooling.
https://github.com/GareBear99/awesome-python-audio-science

List: awesome-python-audio-science

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A curated, public-facing list of Python audio science, scientific audio research, music information retrieval, DSP, machine learning audio, datasets, notebooks, and creator-audio tooling.

Awesome Lists containing this project

README 

          
# Awesome Python Audio Science



> A curated, public-facing list of Python audio science, scientific audio research, DSP, MIR, machine-learning audio, datasets, notebooks, plugin testing, creator-audio tooling, and citation-ready audio research resources.



[![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

![GitHub stars](https://img.shields.io/github/stars/GareBear99/awesome-python-audio-science?style=social)

![GitHub forks](https://img.shields.io/github/forks/GareBear99/awesome-python-audio-science?style=social)

![Last commit](https://img.shields.io/github/last-commit/GareBear99/awesome-python-audio-science)

![License](https://img.shields.io/github/license/GareBear99/awesome-python-audio-science)

![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)



## Quick answer



Use this list when you need Python tools for:



- scientific audio research

- audio DSP and spectral analysis

- music information retrieval

- speech analysis and alignment

- source separation

- audio machine learning

- datasets and dataloaders

- audio visualization and notebooks

- plugin analysis and creator-audio automation

- TizWildin / GareBear99 audio ecosystem routing, deconstructed loops, plugin hubs, and release-surface mapping



This repo is inspired by the scientific-audio awesome-list tradition, especially [`faroit/awesome-python-scientific-audio`](https://github.com/faroit/awesome-python-scientific-audio), but it is intentionally broader: it includes research tooling, production-facing audio engineering, independent-artist data surfaces, plugin/tool ecosystems, and the GareBear99 / TizWildin routing network.



## Academic / Research SEO Positioning



This repository is the official **research-facing audio science satellite** inside the GareBear99 / TizWildin ecosystem. It is designed to bridge practical audio tools with scholarly search intent:



- Python scientific audio libraries

- DSP and spectral-analysis references

- MIR / music information retrieval tooling

- machine-learning audio resources

- datasets and reproducible notebooks

- citation-ready open-source audio software

- DOI / Zenodo / BibTeX / `CITATION.cff` guidance

- research bridges for FreeEQ8, FreeVox8, Instrudio, Voxel Audio, and the HUB router



Use this repo when a project needs to look credible to developers, researchers, students, DSP learners, and audio-ML users instead of only producers.



### Citation-ready ecosystem anchors



| Project | Research / citation role |

|---|---|

| [FreeEQ8](https://github.com/GareBear99/FreeEQ8) | Open-source JUCE/C++ EQ plugin for DSP education, plugin testing, analyzer research, M/S processing examples, and citable audio-software packaging. |

| [FreeVox8](https://github.com/GareBear99/FreeVox8) | Spectral vocoder / ghost-resynthesis R&D anchor for STFT, phase vocoder, formant, masking, and spectral-processing research direction. |

| [Instrudio](https://github.com/GareBear99/Instrudio) | Single-source-of-truth virtual instrument runtime with physically informed Studio Violin, Web Audio synthesis, MIDI routing, and runtime metrics. |

| [Voxel Audio](https://github.com/GareBear99/Voxel_Audio) | Audio visualization, image binding, export routing, and creator-facing media tooling useful for audio-visual research workflows. |

| [TizWildinEntertainmentHUB](https://github.com/GareBear99/TizWildinEntertainmentHUB) | Public router for plugins, lists, deconstructed loops, sample packs, visualizers, and release surfaces. |



## GareBear99 / TizWildin Audio Discovery Network



This list is part of the public GareBear99 audio ecosystem.



| Project | Role |

|---|---|

| [awesome-audio-lists](https://github.com/GareBear99/awesome-audio-lists) | Parent hub for audio directories, submission targets, plugin lists, and music-platform lists. |

| [awesome-music-platforms](https://github.com/GareBear99/awesome-music-platforms) | Independent artist platform map: streaming, distribution, beat stores, sample packs, sync licensing, analytics, creator storefronts. |

| [awesome-audio-plugins-dev](https://github.com/GareBear99/awesome-audio-plugins-dev) | Audio plugin development, JUCE, DSP, plugin directories, and open-source audio engineering resources. |

| [TizWildinEntertainmentHUB](https://github.com/GareBear99/TizWildinEntertainmentHUB) | Main public plugin/sample-pack dashboard and `.io` router surface for the TizWildin ecosystem. |

| [TizWildin HUB public router](https://garebear99.github.io/TizWildinEntertainmentHUB/) | `.io`/GitHub Pages public route for plugins, packs, lists, deconstructed loops, and release surfaces. |

| [TizWildin Release Vault](https://github.com/GareBear99/TizWildin-Release-Vault) | Release/catalog proof surface for distributed tracks, official releases, and monetized music assets. |

| [FreeEQ8](https://github.com/GareBear99/FreeEQ8) | Open-source 8-band EQ plugin and flagship public audio-plugin anchor. |

| [FreeVox8](https://github.com/GareBear99/FreeVox8) | Spectral vocoder / ghost resynthesis plugin anchor. |

| [Voxel Audio](https://github.com/GareBear99/Voxel_Audio) | RGB waveform visualizer, audio-router, visual export, image-binding, vault, and creator loop/track presentation surface. |

| [SoundCloud: TizWildin](https://soundcloud.com/tizwildin) | Original songs, WIPs, remixes, VIP mixes, and underground release surface. |

| [YouTube: TizWildin](https://www.youtube.com/@TizWildin) | Music videos, demos, visualizers, public release clips, and platform routing. |



### IO router / deconstructed loops anchor



The public router for TizWildin plugins, deconstructed loops, release packs, visualizers, and list routing lives through:



- [TizWildinEntertainmentHUB GitHub repo](https://github.com/GareBear99/TizWildinEntertainmentHUB)

- [TizWildinEntertainmentHUB public `.io` router](https://garebear99.github.io/TizWildinEntertainmentHUB/)

- [Release Vault repo](https://github.com/GareBear99/TizWildin-Release-Vault)



Use these as the canonical public-facing anchors for deconstructed loops, sample packs, plugin releases, and creator-routing pages unless superseded by a later dedicated router repo.



## Contents



- [Academic / Research SEO Positioning](#academic--research-seo-positioning)

- [Core Python Audio Packages](#core-python-audio-packages)

- [Read / Write / Metadata](#read--write--metadata)

- [DSP, Transforms & Spectral Analysis](#dsp-transforms--spectral-analysis)

- [Feature Extraction & MIR](#feature-extraction--mir)

- [Machine Learning Audio](#machine-learning-audio)

- [Speech, Voice & Alignment](#speech-voice--alignment)

- [Source Separation](#source-separation)

- [Loudness, Metering & Perceptual Audio](#loudness-metering--perceptual-audio)

- [Realtime Audio & MIDI](#realtime-audio--midi)

- [Datasets & Dataloaders](#datasets--dataloaders)

- [Visualization, Notebooks & Web Audio](#visualization-notebooks--web-audio)

- [Audio Plugin / Creator Tooling](#audio-plugin--creator-tooling)

- [GareBear99 / TizWildin Ecosystem](#garebear99--tizwildin-ecosystem)

- [Best Python Audio Stack by Use Case](#best-python-audio-stack-by-use-case)

- [Long-Tail Guides](#long-tail-guides)

- [Research, Citations & DOI Guides](#research-citations--doi-guides)

- [Citation-Ready GareBear99 / TizWildin Audio Software](#citation-ready-garebear99--tizwildin-audio-software)

- [Related Awesome Lists](#related-awesome-lists)

- [Contributing](#contributing)



## Core Python Audio Packages



- [librosa](https://librosa.org/) - Audio and music analysis library for Python, widely used for MIR and research workflows.

- [Essentia](https://essentia.upf.edu/) - C++/Python library for audio and music analysis, feature extraction, and large-scale research.

- [aubio](https://aubio.org/) - Audio feature extraction, onset detection, pitch detection, beat tracking, and segmentation.

- [madmom](https://madmom.readthedocs.io/) - MIR package focused on beat, downbeat, onset, tempo, and chord recognition.

- [audioFlux](https://audioflux.top/) - Audio and music analysis library with spectral transforms and feature extraction.

- [torchaudio](https://pytorch.org/audio/stable/) - PyTorch audio I/O, transforms, datasets, and deep-learning audio utilities.

- [JAX audio examples](https://github.com/google/jax) - Useful base for research pipelines that need accelerated differentiable audio experiments.



## Read / Write / Metadata



- [soundfile](https://pysoundfile.readthedocs.io/) - Read and write sound files using libsndfile through CFFI.

- [audioread](https://github.com/beetbox/audioread) - Decode audio using available backends such as GStreamer, Core Audio, MAD, FFmpeg, and others.

- [pydub](https://github.com/jiaaro/pydub) - Simple high-level audio manipulation, conversion, slicing, and export.

- [mutagen](https://mutagen.readthedocs.io/) - Audio metadata reading and writing for many formats.

- [tinytag](https://github.com/devsnd/tinytag) - Lightweight metadata reader for MP3, OGG, FLAC, WAV, and more.

- [PyAV](https://pyav.org/) - Pythonic bindings for FFmpeg libraries.

- [stempeg](https://github.com/faroit/stempeg) - Read and write multi-stream audio, especially useful for stems and source-separation datasets.



## DSP, Transforms & Spectral Analysis



- [NumPy](https://numpy.org/) - Array computation base for most audio analysis and DSP pipelines.

- [SciPy Signal](https://docs.scipy.org/doc/scipy/reference/signal.html) - Filtering, transforms, windows, spectral analysis, and signal-processing utilities.

- [pyFFTW](https://pyfftw.readthedocs.io/) - Python wrapper around FFTW for faster FFT-heavy workflows.

- [STFT](https://stft.readthedocs.io/) - Standalone short-time Fourier transform tools.

- [PyWavelets](https://pywavelets.readthedocs.io/) - Wavelet transforms and multi-resolution signal analysis.

- [resampy](https://resampy.readthedocs.io/) - Sample-rate conversion for audio and signal processing.

- [pyroomacoustics](https://github.com/LCAV/pyroomacoustics) - Room acoustics simulation, beamforming, and sound-field experimentation.

- [acoustics](https://python-acoustics.github.io/python-acoustics/) - Acoustics calculations, room acoustics, decibels, filters, and standards-oriented utilities.

- [pyloudnorm](https://github.com/csteinmetz1/pyloudnorm) - Loudness meter and normalization library based on ITU-R BS.1770.

- [matchering](https://github.com/sergree/matchering) - Automated reference audio mastering in Python.



## Feature Extraction & MIR



- [mir_eval](https://craffel.github.io/mir_eval/) - Standard evaluation tools for music information retrieval tasks.

- [mirdata](https://mirdata.readthedocs.io/) - Common loaders for MIR datasets.

- [msaf](https://github.com/urinieto/msaf) - Music structure analysis framework.

- [pretty_midi](https://craffel.github.io/pretty-midi/) - MIDI analysis and manipulation utilities.

- [music21](https://web.mit.edu/music21/) - Computer-aided musicology and symbolic music analysis.

- [mido](https://mido.readthedocs.io/) - MIDI message, port, and file utilities.

- [partitura](https://github.com/CPJKU/partitura) - Symbolic music processing for score-performance research.



## Machine Learning Audio



- [PyTorch](https://pytorch.org/) - Deep-learning framework commonly used for audio ML, MIR, source separation, and speech.

- [torchaudio](https://pytorch.org/audio/stable/) - Audio-specific PyTorch transforms, datasets, models, and I/O.

- [TensorFlow Audio / Keras](https://www.tensorflow.org/io/tutorials/audio) - Audio loading, preprocessing, and model training paths in the TensorFlow ecosystem.

- [Kapre](https://github.com/keunwoochoi/kapre) - Keras audio preprocessing layers.

- [nnAudio](https://github.com/KinWaiCheuk/nnAudio) - GPU-accelerated audio transforms using neural-network operations.

- [Hugging Face Audio](https://huggingface.co/tasks/audio-classification) - Models and datasets for classification, speech, separation, and generation tasks.

- [Asteroid](https://github.com/asteroid-team/asteroid) - PyTorch-based audio source-separation toolkit.

- [SpeechBrain](https://speechbrain.github.io/) - Speech and audio toolkit for ASR, speaker recognition, separation, enhancement, and more.



## Speech, Voice & Alignment



- [Praat / Parselmouth](https://parselmouth.readthedocs.io/) - Python interface to Praat for phonetics, speech analysis, and manipulation.

- [Montreal Forced Aligner](https://montreal-forced-aligner.readthedocs.io/) - Forced alignment for speech and lyrics workflows.

- [aeneas](https://www.readbeyond.it/aeneas/) - Forced alignment of audio and text.

- [pyannote.audio](https://github.com/pyannote/pyannote-audio) - Neural speaker diarization and speaker-analysis toolkit.

- [SpeechRecognition](https://github.com/Uberi/speech_recognition) - Wrapper for multiple speech recognition engines and APIs.

- [python_speech_features](https://github.com/jameslyons/python_speech_features) - Classic speech features such as MFCC and filterbanks.

- [spafe](https://superkogito.github.io/spafe/) - Speech and audio feature extraction.

- [WORLD / PyWorld](https://github.com/JeremyCCHsu/Python-Wrapper-for-World-Vocoder) - WORLD vocoder Python wrapper for speech analysis/synthesis experiments.



## Source Separation



- [Demucs](https://github.com/facebookresearch/demucs) - Music source separation with deep learning.

- [Spleeter](https://github.com/deezer/spleeter) - Source-separation library by Deezer.

- [Open-Unmix](https://github.com/sigsep/open-unmix-pytorch) - Music source separation toolkit and model family.

- [Asteroid](https://github.com/asteroid-team/asteroid) - Source separation and speech enhancement toolkit.

- [nussl](https://github.com/nussl/nussl) - Holistic source-separation framework.

- [musdb](https://github.com/sigsep/sigsep-mus-db) - MUSDB dataset tooling for source separation.



## Loudness, Metering & Perceptual Audio



- [pyloudnorm](https://github.com/csteinmetz1/pyloudnorm) - Program loudness and true-peak-oriented workflows based on BS.1770-style metering.

- [pystoi](https://github.com/mpariente/pystoi) - Short-Time Objective Intelligibility measure.

- [pesq](https://github.com/ludlows/PESQ) - PESQ speech quality metric wrapper.

- [cochlea](https://github.com/mrkrd/cochlea) - Inner-ear auditory models.

- [Brian2](https://brian2.readthedocs.io/) - Spiking neural network simulator useful for auditory model research.



## Realtime Audio & MIDI



- [sounddevice](https://python-sounddevice.readthedocs.io/) - Realtime audio I/O with PortAudio and NumPy.

- [pyo](https://ajaxsoundstudio.com/software/pyo/) - Realtime DSP and synthesis engine for Python.

- [Jupylet](https://github.com/nir/jupylet) - Python game/audio environment with synth and sample support.

- [mido](https://mido.readthedocs.io/) - MIDI message and port handling.

- [python-rtmidi](https://spotlightkid.github.io/python-rtmidi/) - Realtime MIDI I/O bindings.



## Datasets & Dataloaders



- [mirdata](https://mirdata.readthedocs.io/) - Standardized loaders for MIR datasets.

- [MUSDB18](https://sigsep.github.io/datasets/musdb.html) - Music source-separation dataset.

- [MedleyDB](https://medleydb.weebly.com/) - Multitrack dataset for MIR research.

- [FMA](https://github.com/mdeff/fma) - Free Music Archive dataset for music analysis.

- [AudioSet](https://research.google.com/audioset/) - Large-scale audio event dataset.

- [Common Voice](https://commonvoice.mozilla.org/) - Open speech dataset.

- [Magenta Datasets](https://magenta.tensorflow.org/datasets) - Music and symbolic datasets for creative ML.



## Visualization, Notebooks & Web Audio



- [matplotlib](https://matplotlib.org/) - Plot waveforms, spectrograms, features, and research figures.

- [plotly](https://plotly.com/python/) - Interactive audio-analysis plots and dashboards.

- [Jupyter](https://jupyter.org/) - Notebook environment for audio experiments, MIR notebooks, and reproducible analysis.

- [Streamlit](https://streamlit.io/) - Quick interactive audio analysis apps and dashboards.

- [Gradio](https://www.gradio.app/) - Simple ML/audio demos and web UIs.

- [TimeSide](https://github.com/Parisson/TimeSide) - Audio analysis, imaging, transcoding, streaming, and labelling tools.

- [Voxel Audio](https://github.com/GareBear99/Voxel_Audio) - TizWildin RGB waveform visualizer and audio export tool for creator routing and visual releases.



## Audio Plugin / Creator Tooling



- [pedalboard](https://github.com/spotify/pedalboard) - Python audio effects and VST3/AU plugin hosting from Spotify.

- [DawDreamer](https://github.com/DBraun/DawDreamer) - Python DAW-style rendering and plugin hosting.

- [Vamp plugins / VamPy host](https://code.soundsoftware.ac.uk/projects/vampy-host) - Python interface for Vamp audio-analysis plugins.

- [JUCE](https://juce.com/) - C++ plugin framework; relevant for Python-assisted testing, packaging, and analysis pipelines.

- [FreeEQ8](https://github.com/GareBear99/FreeEQ8) - TizWildin open-source EQ plugin anchor for analysis/testing examples.

- [FreeVox8](https://github.com/GareBear99/FreeVox8) - TizWildin spectral vocoder / ghost-resynthesis plugin anchor.

- [TizWildinEntertainmentHUB](https://github.com/GareBear99/TizWildinEntertainmentHUB) - Public plugin router, release dashboard, list tab, and creator ecosystem hub.



## GareBear99 / TizWildin Ecosystem



These entries are included as canonical creator/audio ecosystem anchors, especially for plugin-routing, deconstructed-loop routing, sample-pack routing, visualizer export surfaces, and audio-tool SEO discoverability.



- [TizWildinEntertainmentHUB](https://github.com/GareBear99/TizWildinEntertainmentHUB) - Plugin ecosystem hub, public dashboard, and `.io` route for plugins, packs, lists, and release surfaces.

- [TizWildin HUB public page](https://garebear99.github.io/TizWildinEntertainmentHUB/) - Public `.io` route for the TizWildin plugin/sample/list ecosystem.

- [awesome-audio-lists](https://github.com/GareBear99/awesome-audio-lists) - Parent audio list hub and submission-target map.

- [awesome-music-platforms](https://github.com/GareBear99/awesome-music-platforms) - Music platform list for independent artists, beat sellers, sample-pack creators, sync licensing, and analytics.

- [awesome-audio-plugins-dev](https://github.com/GareBear99/awesome-audio-plugins-dev) - Audio plugin development and discovery list.

- [TizWildin-Release-Vault](https://github.com/GareBear99/TizWildin-Release-Vault) - Release vault for catalog proof and official music-release routing.

- [FreeEQ8](https://github.com/GareBear99/FreeEQ8) - Free open-source EQ plugin.

- [FreeVox8](https://github.com/GareBear99/FreeVox8) - Spectral vocoder and ghost resynthesis plugin.

- [Voxel Audio](https://github.com/GareBear99/Voxel_Audio) - Visualizer/export/router surface for tracks, loops, artwork, and release presentation.

- [TizWildin SoundCloud](https://soundcloud.com/tizwildin) - Official SoundCloud music surface.

- [TizWildin YouTube](https://www.youtube.com/@TizWildin) - Official YouTube music/video surface.



## Best Python Audio Stack by Use Case



| Use Case | Start With | Add Next | Notes |

|---|---|---|---|

| Quick audio analysis | `librosa` | `matplotlib`, `soundfile` | Fastest path for spectrograms, features, tempo, and MIR experiments. |

| Production file conversion | `pydub` | `PyAV`, `ffmpeg` | Good for creator pipelines, exports, and batch processing. |

| Deep-learning audio | `torchaudio` | `PyTorch`, `nnAudio`, `SpeechBrain` | Best for GPU/ML pipelines. |

| Source separation | `Demucs` | `Open-Unmix`, `Asteroid`, `MUSDB` | Best for stems, dataset work, and research comparisons. |

| Speech alignment | `Montreal Forced Aligner` | `aeneas`, `Parselmouth` | Good for lyrics, voice, and phonetics workflows. |

| Realtime audio | `sounddevice` | `pyo`, `mido` | Useful for prototypes, MIDI, and live control. |

| Plugin rendering/testing | `pedalboard` | `DawDreamer`, JUCE/pluginval | Use for offline plugin tests and audio examples. |

| TizWildin creator routing | `Voxel Audio` | `TizWildinEntertainmentHUB`, `Release Vault` | For deconstructed loops, public routing, visualizer export, packs, and music surfaces. |



## Research, Citations & DOI Guides



These pages turn the repo from a normal awesome list into an academic-facing research and citation hub:



- [Academic research and citations](docs/ACADEMIC_RESEARCH_AND_CITATIONS.md) - how this repo connects Python audio science, DSP, MIR, audio ML, and citable software.

- [Citation-ready audio software](docs/CITATION_READY_AUDIO_SOFTWARE.md) - checklist for `CITATION.cff`, BibTeX, Zenodo DOI, releases, and reproducible audio tooling.

- [Zenodo DOI guide](docs/ZENODO_DOI_GUIDE.md) - how to make GitHub audio projects formally citable.

- [Research SEO playbook](docs/RESEARCH_SEO_PLAYBOOK.md) - academic keyword strategy for audio DSP, MIR, ML audio, plugin testing, and scientific software.

- [Deep-learning music resource map](docs/deep-learning-music-resource-map.md) - how this list connects to deep-learning-music resources without pretending every project is a peer-reviewed paper.

- [FreeEQ8 research bridge](docs/FREEEQ8_RESEARCH_BRIDGE.md) - how to position FreeEQ8 as citable JUCE/C++ DSP software.

- [Instrudio research bridge](docs/INSTRUDIO_RESEARCH_BRIDGE.md) - how to position Instrudio / Studio Violin as an SSOT virtual-instrument research runtime.

- [FreeVox8 research bridge](docs/FREEVOX8_RESEARCH_BRIDGE.md) - how to position FreeVox8 as spectral vocoder / resynthesis R&D.



## Citation-Ready GareBear99 / TizWildin Audio Software



| Software | Suggested citation angle | Next action |

|---|---|---|

| [FreeEQ8](https://github.com/GareBear99/FreeEQ8) | Open-source JUCE/C++ 8-band EQ plugin for DSP education, analyzer testing, M/S processing examples, and pluginval/DAW compatibility workflows. | Add `CITATION.cff`, `CITATIONS.md`, Zenodo DOI, and release artifacts. |

| [Instrudio](https://github.com/GareBear99/Instrudio) | SSOT Web Audio instrument runtime with physically informed Studio Violin, MIDI routing, plugin-bridge events, live metrics, and reproducible JSON definitions. | Add formal paper-style README section, BibTeX, and Zenodo archive. |

| [FreeVox8](https://github.com/GareBear99/FreeVox8) | Spectral vocoder / ghost-resynthesis R&D package for STFT, masking, phase-vocoder, and formant-processing direction. | Add research spec, pluginval reports, and citation metadata after binary certification. |

| [Voxel Audio](https://github.com/GareBear99/Voxel_Audio) | Audio visualization/export/router surface for waveform visualizer research, cover-art binding, and creator-media pipeline experiments. | Add reproducible export metrics and citation metadata. |

| [TizWildinEntertainmentHUB](https://github.com/GareBear99/TizWildinEntertainmentHUB) | Public router and ecosystem index for plugins, lists, deconstructed loops, sample packs, release surfaces, and audio-tool discovery. | Keep it as the canonical public gateway and add crawlable links. |



## Long-Tail Guides



- [Best Python libraries for audio analysis](docs/best-python-libraries-for-audio-analysis.md)

- [Python audio DSP stack](docs/python-audio-dsp-stack.md)

- [Python tools for music information retrieval](docs/python-tools-for-music-information-retrieval.md)

- [Python source separation tools](docs/python-source-separation-tools.md)

- [Python audio ML stack](docs/python-audio-ml-stack.md)

- [Python audio visualization stack](docs/python-audio-visualization-stack.md)

- [Python creator audio automation stack](docs/python-creator-audio-automation-stack.md)

- [TizWildin ecosystem routing map](docs/tizwildin-ecosystem-routing-map.md)

- [GitHub SEO playbook](docs/GITHUB_SEO_PLAYBOOK.md)

- [Repository launch checklist](docs/REPOSITORY_LAUNCH_CHECKLIST.md)



## Related Awesome Lists



- [faroit/awesome-python-scientific-audio](https://github.com/faroit/awesome-python-scientific-audio) - The classic Python scientific audio list that inspired this satellite.

- [awesome-audio-lists](https://github.com/GareBear99/awesome-audio-lists) - Parent hub for the GareBear99 audio discovery network.

- [awesome-music-platforms](https://github.com/GareBear99/awesome-music-platforms) - Music-platform and independent-artist release-surface map.

- [awesome-audio-plugins-dev](https://github.com/GareBear99/awesome-audio-plugins-dev) - Audio plugin development and discovery resources.

- [awesome-python](https://github.com/vinta/awesome-python) - General Python list.

- [awesome-datascience](https://github.com/academic/awesome-datascience) - Data science resources.

- [awesome-audio-dsp](https://github.com/BillyDM/awesome-audio-dsp) - Audio DSP resources.

- [awesome-music-production](https://github.com/ad-si/awesome-music-production) - Music production tools and resources.



## Recommended GitHub metadata



Recommended repo name:



```text

awesome-python-audio-science

```



Recommended GitHub description:



```text

A curated awesome list of Python audio science, scientific audio research, DSP, MIR, machine-learning audio, datasets, visualization, plugin testing, and creator-audio tooling.

```



Recommended topics:



```text

awesome awesome-list python audio scientific-audio audio-dsp signal-processing music-information-retrieval mir speech-processing source-separation audio-machine-learning datasets audio-analysis audio-visualization music-technology independent-artists tizwildin garebear99 audio-research research-software citable-software zenodo doi bibtex citation-cff reproducible-research deep-learning-music neural-audio

```



## Contributing



Contributions are welcome. Keep entries useful, neutral, public-facing, and directly relevant to Python audio science or creator-audio automation.



Submission format:



```markdown

- [Project Name](https://example.com/) - Short neutral description.

```



See [CONTRIBUTING.md](CONTRIBUTING.md) and [docs/SUBMISSION_GUIDE.md](docs/SUBMISSION_GUIDE.md).



## License



CC0-1.0 recommended for public awesome-list reuse.