Digital watermarking is a very recent research area. Digital audio watermarking is a method to embed or hide the Watermark (Information signal) into a digital signal i.e. Image, audio, text or video data. The watermark is difficult to remove from the audio signal. If the signal is copied, the information or watermark is also carried in the copy. A signal may carry several different watermarks a...

In this paper, an innovative watermarking scheme for audio signal based on genetic algorithms (GA) is proposed. Designing an optimal audio watermarking system is an open difficult issue since its two basic performance measures, i.e., imperceptibility and robustness. So, an optimal audio watermarking scheme needs to optimally balance both imperceptibility and robustness. In order to realize such...

This audio quality measurement Application Note is geared towards describing the methods for measurement of key audio specifications. Each analysis technique described here in, can be applied to audio ADCs, DACs, Analog Mixers, or any signal within the audio band. Audio quality is typically gauged by three main components. They are Signal to Noise Ratio, Total Harmonic Distortion, and Frequency...

A modular real-time PC-based audio processing software tool has been developed which offers a high degree of user control, intended for use by audio effect developers, signal processing engineers, sound designers, musicians, and educators. The key technical features are described, followed by a range of example applications in the field of signal processing and audio effect design.

This paper presents a audio watermark detection scheme using the undetermined independent analysis. The proposed detection scheme removes audio spectrum from the watermarked audio signal. And then, ICA-based detector estimates the hidden independent sources from the received watermarked signal using BSS for underdetermined mixtures based on ICA.

This audio quality measurement Application Note is geared towards describing the methods for measurement of key audio specifications. Each analysis technique described here in, can be applied to audio ADCs, DACs, Analog Mixers, or any signal within the audio band. Audio quality is typically gauged by three main components. They are Signal to Noise Ratio, Total Harmonic Distortion, and Frequency...

In the framework of audio signal analysis, there have been recent significant advances in two directions: sparse and structured representation. In fact, sparse decompositions of audio signals are shown to be effective, and appear to be extremely useful in many signal processing applications: compression, source separation, noise reduction... A second point of view tries to take advantage of the...

Speech signal analysis is one of the important areas of research in multimedia applications. Discrete Wavelet technique is effectively reduces the unwanted higher or lower order frequency components in a speech signal. Wavelet-based algorithm for audio de-noising is worked out. We focused on audio signals corrupted with white Gaussian noise which is especially hard to remove because it is locat...

Audio classification is very important in many audio applications so that different audio signal can be processed appropriately. We propose an audio classification scheme which will categorise audio based on a number of audio features. These features include silence ratio, spectral centroid, harmonicity and pitch. Our preliminary experiments with silence ratio feature produce very promising cla...

Missing data in corrupted audio recordings poses a challenging problem for audio signal processing. In this paper we present an approach that allows us to estimate missing values in the time-frequency domain of audio signals. The proposed approach, based on the Nonnegative Hidden Markov Model, enables more temporally coherent estimation for the missing data by taking into account both the spect...