AAC encoding detection and bitrate estimation using a convolutional neural network

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.

DOI: 10.1109/ICASSP.2016.7472041

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Cite this paper

@article{Seichter2016AACED, title={AAC encoding detection and bitrate estimation using a convolutional neural network}, author={Daniel Seichter and Luca Cuccovillo and Patrick Aichroth}, journal={2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year={2016}, pages={2069-2073} }