music-audio-tagging-at-scale-models
Audio tagging research
Research on end-to-end learning for music audio tagging using large datasets and different front-end paradigms.
Tensorflow implementation of the models used in "End-to-end learning for music audio tagging at scale"
148 stars
6 watching
19 forks
Language: Python
last commit: about 5 years ago Related projects:
Repository | Description | Stars |
---|---|---|
jordipons/eusipco2017 | Research code for music auto-tagging using deep learning and feature extraction | 23 |
jongpillee/musictagging_msd | This project is an audio classification system trained on the MSD tagging dataset, enabling automatic tagging of music files with relevant genres and styles. | 7 |
microsoft/pengi | An Audio Language Model framework that uses transfer learning to generate text from audio inputs | 290 |
balavenkatesh3322/audio-pretrained-model | A collection of pre-trained audio and speech models for various applications | 182 |
ibm/max-audio-classifier | Identifies sounds in short audio clips using machine learning and PCA transformation | 153 |
yuangongnd/whisper-at | An audio processing model that adds audio event tagging capabilities to an existing speech recognition system with minimal additional computational cost. | 321 |
jthorborg/ape | An Audio Programming Environment with support for AU and DSP plugins | 14 |
iver56/audiomentations | Library for audio data augmentation used in machine learning | 1,873 |
yuangongnd/ltu | An audio and speech large language model implementation with pre-trained models, datasets, and inference options | 385 |
kristijanbartol/deep-music-tagger | Classifies music genres using a deep neural network model trained on a large audio dataset | 67 |
soundio/soundstage | A graph object model and sequencing engine for Web Audio processing graphs | 65 |
soerenab/audiomnist | This project provides an implementation of a deep learning framework to classify audio signals and offers insights into the model's decision-making process using Explainable Artificial Intelligence (AI) techniques. | 347 |
ynop/audiomate | A Python library for handling audio datasets, providing tools for accessing, manipulating, and preparing data for machine learning tasks. | 131 |
cpjku/madmom | A Python audio signal processing library used in music information retrieval tasks. | 1,347 |
keunwoochoi/auralisation | Reconstructs audio features learned by convolutional neural networks into audible sounds | 42 |