Robust Speech Hashing for Digital Audio Forensics

Robust Audio Hashing for Content Identification

Nowadays most audio content identification systems are based on watermarking technology. In this paper we present a different technology, referred to as robust audio hashing. By extracting robust features and translating them into a bit string, we get an object called a robust hash. Content can then be identified by comparing hash values of a received audio clip with the hash values of previous...

A Perceptual Audio Hashing Algorithm: A Tool for Robust Audio Identification and Information Hiding

Assuming that watermarking is feasible (say, against a limited set of attacks of significant interest), current methods use a secret key to generate and embed a watermark. However, if the same key is used to watermark different items, then each instance may leak partial information and it is possible that one may extract the whole secret from a collection of watermarked items. Thus it will be i...

Robust and efficient digital audio watermarking using audio content analysis

Robust speech / music classification in audio documents

This paper deals with a novel approach to speech / music segmentation based on four original features: 4 Hz modulation energy, modulation entropy and two segmental parameters. The relevance of these features is evaluated in a first experiment based on a development corpus composed of collected samples of speech and music. Another corpus is employed to verify the robustness of the employed algor...

Digital Forensics to Intelligent Forensics

In this paper we posit that current investigative techniques—particularly as deployed by law enforcement, are becoming unsuitable for most types of crime investigation. The growth in cybercrime and the complexities of the types of the cybercrime coupled with the limitations in time and resources, both computational and human, in addressing cybercrime put an increasing strain on the ability of d...