Classifiying audio with #artificial-intelligence can be done using #TensorFlow's YAMNet model. YAMNet is a deep neural network that predict 521 audio event classes. It has been trained on the [AudioSet](https://research.google.com/audioset/) dataset from Google/Youtube. Paradoxically, sound classification is done by doing image analysis. Sound can have at least three kind of visual representation : - The Waveform - The Fourier Transofrm - The [Mel Spectogram](Mel%20Spectogram.md) YAMNet is using TensorFlow to perform deep-learning algorithms on Mel Spectogram representations in order to achieve things like pattern recognition, thus the usage for audio classification. Going further : - [Sound classification using YAMNet - TensorFlow](https://www.tensorflow.org/hub/tutorials/yamnet) - [Pitch Detection using SPICE - TensorFlow](https://www.tensorflow.org/hub/tutorials/spice)