ebouteillon/freesound-audio-tagging-2019
Freesound Audio Tagging 2019
This solution helps machine learning practitioners automatically categorize audio recordings into multiple labels, even with limited manually-labeled data. It takes in collections of audio clips and associated labels, then outputs a system capable of accurately predicting what sounds are present in new, unseen audio. This is ideal for researchers or engineers working on advanced audio analysis projects.
No commits in the last 6 months.
Use this if you need a high-performing system to classify environmental sounds, animal sounds, or other audio events from raw sound files, especially when you have a mix of clean and noisy labeled data.
Not ideal if you're looking for a simple tool to tag a small number of audio files manually or if your primary goal is speech recognition.
Stars
95
Forks
15
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 28, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ebouteillon/freesound-audio-tagging-2019"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
aqibsaeed/Urban-Sound-Classification
Urban sound classification using Deep Learning
spotify/realbook
Easier audio-based machine learning with TensorFlow.
ArmDeveloperEcosystem/ml-audio-classifier-example-for-pico
ML Audio Classifier Example for Pico 🔊🔥🔔
IliaZenkov/sklearn-audio-classification
An in-depth analysis of audio classification on the RAVDESS dataset. Feature engineering,...
mimbres/neural-audio-fp
Official implementation of Neural Audio Fingerprint (ICASSP 2021)