Authors: ARIAS Camila and IBARRA Kevin
The purpose of this notebook is to explain how SoundNet works (maths, code, and experiments). Soundnet was developed in 2016 in order to use the natural synchronization between pictures and sounds to learn an acoustic representation from a large number of unlabeled videos, it means to get important features of the sound which allow us to depict them. Other studies are focused on features such as spectrograms and MFCC, on another hand, Soundnet is focused on the natural sounds.
- High level features and sound classifier