Abstract: Prior works on re-quantization detection were mainly focused on still images and videos, implying that the involved quantization is uniform. In this paper, we examine non-uniform re-quantization, and then investigate the automatic detection of re-compressed speech signals. Based on Fisher Linear Discriminant (FLD), two detection algorithms are described in the time-domain and in the DFT-domain respectively. Comparative experiments indicate that both detection algorithms produce reliable results with AUC values higher than 0.9744 for a set of different experimental setups. In general, time-domain detection performs slightly better than DFT-domain detection. However, the latter is superior in the less dimensionality of input vectors.

  url          = {http://portal.acm.org/citation.cfm?id=1854229.1854239},
  booktitle    = {ACM Workshop on Multimedia and Security},
  author       = {Xiaoying Feng},
  location     = {Rome, Italy},
  year         = {2010},
  title        = {{FLD}-based detection of re-compressed speech signals},
  pages        = {43-48},