Towards content-based audio fragment authentication

Abstract

Audio authentication is a technique to protect the integrity and originality of audio signals. Due to the long duration, it is often desirable to authenticate only a segment of audio signal. To the authors' knowledge, this important issue has not been seriously researched so far. In this paper, a novel authentication algorithm is proposed for the purpose of audio fragment authentication. SIFT descriptor originated from computer vision field is introduced and calculated on audio spectrogram to accomplish the tasks of fragment alignment, time-domain blocking, cropping and inserting identification etc. Experiments show reliable discrimination between admissible and malicious manipulations, precise tamper localization and classification.

SIFT-based local spectrogram image descriptor: a novel feature for robust music identification

“…In some applications such as content-based audio authentication, it might be useful to know whether and how seriously an input music excerpt has been time-stretched or pitch-shifted [42]. In spite of this, to our knowledge, few related works have been reported in the literature.…”

Speech Perception Hash Authentication Algorithm Based on Immittance Spectral Pairs

“…Linear Prediction Analysis. In 1967, Japanese scientists Itakura and others for the first application of linear prediction technique [15] in speech, in the various speech processing technology, linear prediction can be applied to a variety of basic speech parameter estimates, such as pitch period, spectral characteristics function, etc.…”