Download Multi-channel Audio Information Hiding We consider a method of hiding many audio channels in one host signal. The purpose of this is to provide a ‘mix’ that incorporates information on all the channels used to produce it, thereby allowing all, or, at least some channels to be stored in the mix for later use (e.g. for re-mixing and/or archiving). After providing an overview of some recently published audio water marking schemes in the time and transform domains, we present a method that is based on using a four least significant bits scheme to embed five MP3 files into a single 16-bit host WAV file without incurring any perceptual audio distortions in either the host data or embedded files. The host WAV file is taken to be the final mix associated with the original multi-channel data before applying minimal MP3 compression (WAV to MP3 conversion), or, alternatively, an arbitrary host WAV file into which other multi-channel data in an MP3 format is hidden. The embedded information can be encrypted and/or the embedding locations randomized on a channelby-channel basis depending on the security protocol desired by the user. The method is illustrated by providing example m-code for interested readers to reproduce the results obtained to date and as a basis for further development.
Download Simulation of Textured Audio Harmonics Using Random Fractal Phaselets We present a method of simulating audio signals using the principles of random fractal geometry which, in the context of this paper, is concerned with the analysis of statistically self-affine ‘phaselets’. The approach is used to generate audio signals that are characterised by texture and timbre through the Fractal Dimension such as those associated with bowed stringed instruments. The paper provides a short overview on potential simulation methods using Artificial Neural Networks and Evolutionary Computing and on the problems associated with using a deterministic approach based on solutions to the acoustic wave equation. This serves to quantify the origins of the ‘noise’ associated with multiple scattering events that characterise texture and timbre in an audio signal. We then explore a method to compute the phaselet of a phase signal which is the primary phase function from which a phase signal is, to a good approximation, a periodic replica and show that, by modelling the phaselet as a random fractal signal, it can be characterised by the Fractal Dimension. The Fractal Dimension is then used to synthesise a phaselet from which the phase function is computed through multiple concatenations of the phaselet. The paper provides details of the principal steps associated with the method considered and examines some example results, providing a URL to m-coded functions for interested readers to repeat the results obtained and develop the algorithms further.