Codec independent lossy audio compression detection

Romain Hennequin, Jimena Royo-Letelier, Manuel Moussallam

Abstract: In this paper, we propose a method for detecting marks of lossy compression encoding, such as MP3 or AAC, from PCM audio. The method is based on a convolutional neural network (CNN) applied to audio spectrograms and trained with the output of various lossy audio codecs and bitrates. Our method shows good performances on a large database and robustness to codec type and resampling.