Robust audio hashing for audio identification

We propose and evaluate three new perceptual audio hash functions. These hash functions are based on a concise description of the time-frequency characteristics. This information can be extracted from the time series of frame-by-frame fundamental period or from the singular value decomposition of the mel frequency cepstral parameters. Experiments show that the proposed perceptual hash functions are both robust and unique.