Detection of clipping in coded speech signals

In order to exploit the full dynamic range of communications and recording equipment, and to minimise the effects of noise and interference, input gain to a recording device is typically set as high as possible. This often leads to the signal exceeding the input limit of the equipment resulting in clipping. Communications devices typically rely on codecs such as GSM 06.10 to compress voice signals into lower bitrates. Although detecting clipping in a hard-clipped speech signal is straightforward due to the characteristic flattening of the peaks of the waveform, this is not the case for speech that has subsequently passed through a codec. We describe a novel clipping detection algorithm based on amplitude histogram analysis and least squares residuals which can estimate the clipped samples and the original signal level in speech even after the clipped speech has been perceptually coded.