music-demixing-challenge-starter-kit
librosa
| music-demixing-challenge-starter-kit | librosa | |
|---|---|---|
| 1 | 14 | |
| 132 | 6,699 | |
| 3.8% | 1.4% | |
| 0.0 | 7.2 | |
| almost 3 years ago | 24 days ago | |
| Python | Python | |
| MIT License | ISC License |
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music-demixing-challenge-starter-kit
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Sound source separation (Music Demixing) challenge by Sony | Easy baselines
There are some great baselines to get started easily: https://github.com/AIcrowd/music-demixing-challenge-starter-kit
librosa
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Open Source Libraries
librosa/librosa: Python library for audio and music analysis
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A Cross-Platform library for audio spectrogram and feature extraction, support mobile real-time computing
How does this compare to mature libraries for other platforms like librosa?
- Precious Advices About AI-supported Audio Classification Model
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What are the common audio feature tool libraries in python?
I use librosa now. What other useful audio feature extraction libraries are there?
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Looking for a program that will examine a folder full of mp3s or flacs and list out ones with lower or higher than average volume
librosa can do that easily but I think there is an easier way to find what are you looking for:
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Get amplitude of every audio frame of .wav
I have a .wav file, and using python, I'd like to get a list of every audio frame where the amplitude is at the resting position. How could I achieve this? I think the librosa library could do such a thing, but I'm struggling to find exactly how to do it. Any help would be greatly appreciated, thank you.
- Show HN: I'm building a browser-based DAW
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AUDIO ANALYSIS WITH LIBROSA
Librosa is a Python package developed for music and audio analysis. It is specific on capturing the audio information to be transformed into a data block. However, the documentation and example are good to understand how to work with audio data science projects.
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AUDIO CLASSIFICATION USING DEEP LEARNING
Hello! welcome once again to the continuation of the last blog post about audio analysis using the Librosa python library, if you missed this article don't worry here you can enjoy audio analysis techniques with Librosa.
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DATA AUGMENTATION IN NATURAL LANGUAGE PROCESSING
Changing pitch of the audio:- in this technique python package for audio analysis like Librosa is the best tool to go with, by adding effect on the audio pitch to create new audio data.
What are some alternatives?
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
pyAudioAnalysis - Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
pydub - Manipulate audio with a simple and easy high level interface
spotify-downloader - Download your Spotify playlists and songs along with album art and metadata (from YouTube if a match is found).
essentia - C++ library for audio and music analysis, description and synthesis, including Python bindings
mkdocs-material-boilerplate - MkDocs Material Boilerplate (Starter Kit) - Deploy documentation to hosting platforms (Netlify, GitHub Pages, GitLab Pages, and AWS Amplify Console) with Docker, pipenv, and GitHub Actions.
kapre - kapre: Keras Audio Preprocessors
sidewinder - Django starter kit that focuses on good defaults, developer experience, and deployment. Updated for Django 5.
beets - music library manager and MusicBrainz tagger
moseca - A Streamilt web app for music source separation & karaoke
audioread - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding for Python