The authors offer an introductory walk-through of professional audio signal measurement and visualisation using free software. Many users of audio software at some time face problems that requires reliable measurement. The presentation focuses on the SiSco.lv2 (Simple Audio Signal Oscilloscope) and the Meters.lv2 (Audio Level Meters) LV2 plugins, which have been developed open-source since Augu...

adapted from Noll (2000) Audio compression or audio coding algorithms are used to obtain compact digital representations of high-fidelity (wideband) audio signals for the purpose of efficient transmission or storage. The central objective in audio coding is to represent the signal with a minimum number of bits while achieving transparent signal reproduction, i.e., generating output audio that c...

A data transmission framework is proposed to embed digital data into an audio signal in a perceptually undetectable or almost undetectable way. The resulting signal can be reproduced as is with no loss of acoustic quality; the embedded data can be exactly retrieved at the decoder. The transmission process exploits the perceptual redundancy of the audio signal to conceal the acoustic impact of t...

Digital audio watermarking is a technique for embedding additional data along with audio signal. Embedded data is used for copyright owner identification. A number of audio watermarking techniques are proposed. These techniques exploit different ways in order to embed a robust watermark and to maintain the original audio signal fidelity. This paper makes a tutorial in general digital watermarki...

This paper reviews Binaural Cue Coding (BCC). BCC is a lossy technique for either reducing either a number of source signals or a multichannel audio signal to one audio channel plus side information. In the case when a number of source signals (e.g. separately recorded instruments) are reduced to one audio channel plus side information, the BCC synthesis allows rendering of each source as if th...

This paper presents a statistical approach to sound texture modeling based on a singular value analysis of spectral features or an eigenvector analysis of their similarity matrix. Using dimension reduction techniques we perform grouping of the signal into similar sounding audio segments that are recurrent in time. The method allows an automatic segmentation of audio signal into larger groups of...