![TensorFlow Requirement: 1.x](https://img.shields.io/badge/TensorFlow%20Requirement-1.x-brightgreen) ![TensorFlow 2 Not Supported](https://img.shields.io/badge/TensorFlow%202%20Not%20Supported-%E2%9C%95-red.svg) # Models for AudioSet: A Large Scale Dataset of Audio Events This repository provides models and supporting code associated with [AudioSet](http://g.co/audioset), a dataset of over 2 million human-labeled 10-second YouTube video soundtracks, with labels taken from an ontology of more than 600 audio event classes. AudioSet was [released](https://research.googleblog.com/2017/03/announcing-audioset-dataset-for-audio.html) in March 2017 by Google's Sound Understanding team to provide a common large-scale evaluation task for audio event detection as well as a starting point for a comprehensive vocabulary of sound events. For more details about AudioSet and the various models we have trained, please visit the [AudioSet website](http://g.co/audioset) and read our papers: * Gemmeke, J. et. al., [AudioSet: An ontology and human-labelled dataset for audio events](https://research.google.com/pubs/pub45857.html), ICASSP 2017 * Hershey, S. et. al., [CNN Architectures for Large-Scale Audio Classification](https://research.google.com/pubs/pub45611.html), ICASSP 2017 If you use any of our pre-trained models in your published research, we ask that you cite [CNN Architectures for Large-Scale Audio Classification](https://research.google.com/pubs/pub45611.html). If you use the AudioSet dataset or the released embeddings of AudioSet segments, please cite [AudioSet: An ontology and human-labelled dataset for audio events](https://research.google.com/pubs/pub45857.html). ## Contact For general questions about AudioSet and these models, please use the [audioset-users@googlegroups.com](https://groups.google.com/forum/#!forum/audioset-users) mailing list. For technical problems with the released model and code, please open an issue on the [tensorflow/models issue tracker](https://github.com/tensorflow/models/issues) and __*assign to @plakal and @dpwe*__. Please note that because the issue tracker is shared across all models released by Google, we won't be notified about an issue unless you explicitly @-mention us (@plakal and @dpwe) or assign the issue to us. ## Credits Original authors and reviewers of the code in this package include (in alphabetical order): * DAn Ellis * Shawn Hershey * Aren Jansen * Manoj Plakal