AAC Encoding Detection and Bitrate Estimation Using a Convolutional Neural Network

Daniel Seichter1, Luca Cuccovillo2, Patrick Aichroth3

  • 1Ilmenau University of Technology
  • 2Fraunhofer IDMT
  • 3Fraunhofer Institute for Digital Media Technology

Details

13:30 - 15:30 | Tue 22 Mar | Poster Area G | IFS-P1.7

Session: Multimedia Forensics

Abstract

In this paper, we propose a new method for AAC encoding detection and bitrate estimation from PCM material. The algorithm is based on a Convolutional Neural Network that can distinguish between eight different bitrates. It achieves an average accuracy of 94.65% by analysis of only 116.10 ms of content.