This is a repo for CS221 Audio Tagging Project.
IRMAS Website with a paper and a Phd thesis
Freesound General-Purpose Audio Tagging Challenge
Types of classification algorithms in Machine Learning
How to teach Neural Networks to detect everyday sounds
fasst for audio source seperation
| Name | Link | With Paper | With Code | Methods Used |
|---|---|---|---|---|
| A Comparison of Sound Segregation Techniques for Predominant Instrument Recognition in Musical Audio Signals | http://ismir2012.ismir.net/event/papers/559_ISMIR_2012.pdf | Yes | No | |
| Instrument-Classification-of-IRMAS-Dataset | https://github.com/iooops/Instrument-Classification-of-IRMAS-Dataset | Yes | Yes | Bagging, Random Forest, Decision Tree Classifier, Naive Bayes, K nearest neighbours |
| A Single Predominant Instrument Recognition of Polyphonic Music Using CNN-based Timbre Analysis | https://www.sciencepubco.com/index.php/ijet/article/view/19388 | Yes | No | CNN |
| Automatic Instrument Identification in Polyphonic Music | https://github.com/glennq/instrument-recognition | Yes | Yes | CNN |
| Deep convolutional neural networks for predominant instrument recognition in polyphonic music | https://arxiv.org/pdf/1605.09507.pdf | Yes | No | CNN |
| General-purpose Tagging Of Freesound Audio With Audioset Labels | https://arxiv.org/pdf/1807.09902.pdf | Yes | No | CNN |
| Audio Tagging With Connectionist Temporal Classification Model Using Sequential Labelled Data | https://arxiv.org/abs/1808.01935 | Yes | No | CRNN, CTC |
| End-to-end learning for music audio tagging at scale | http://www.jordipons.me/apps/music-audio-tagging-at-scale-demo/ | Yes | Yes | CNN |
| Automatic Tagging of Audio: The State-of-the-Art | http://tbertinmahieux.com/Papers/machineaudition10.pdf | Yes | No | SVM, Boosting, Gaussian mixture, HGMM |
| Music Auto-Tagger | https://github.com/keunwoochoi/music-auto_tagging-keras#credits | Yes | Yes | CNN, CRNN |
| Kaggle - Freesound General-Purpose Audio Tagging Challenge | https://github.com/sainathadapa/kaggle-freesound-audio-tagging | Yes | Yes | MobileNetV2? |
| A Survey of Sound Classification Using Classic Methods and Deep Learning | https://web.stanford.edu/class/cs221/2018/restricted/posters/franalli/poster.pdf | Yes(poster) | No | KNN, SVM, Random Forest, CNN |
| Urban Sound Classification | https://github.com/aqibsaeed/Urban-Sound-Classification | Yes | Yes | CNN |