This paper presents a novel watermarking technique for digital audio signals. A visually recognizable binary image served as a watermark is embedded into an audio signal in discrete cosine transform domain. In order to enhance robustness and make good use of masking characteristics of the audio signal, the techniques of pseudo-random permutation and energy-based permutation are used during wate...

Audio signal recovery is a common problem in digital audio restoration field, because of corrupted samples that must be replaced. In this paper a subbands architecture is presented for audio signal recovery, using neural nonlinear prediction based on adaptive spline neural networks. The experimental results show the mean square reconstruction error, and maximum error obtained with increasing ga...

Parametric-stereo coding is a technique to efficiently code a stereo audio signal as a monaural signal plus a small amount of parametric overhead to describe the stereo image. The stereo properties are analyzed, encoded, and reinstated in a decoder according to spatial psychoacoustical principles. The monaural signal can be encoded using any (conventional) audio coder. Experiments show that the...

In this paper we introduce a technique to embed context-based information into an audio signal and to extract this information from the signal during playback. Context-based information can be any kind of data related to the audio signal such as the lyrics of a song or the score of a piece of music. A typical application will display the extracted information. Techniques from lossy audio compre...

Steganography is the art of message hiding in a cover signal without attracting attention. The requirements of the good steganography algorithm are security, capacity, robustness and imperceptibility, all them are contradictory, therefore, satisfying all together is not easy especially in audio cover signal because human auditory system (HAS) has high sensitivity to audio modification. In this ...

In this paper, we investigate the derivation of musical structures directly from signal analysis with the aim of generating visual and audio summaries. From the audio signal, we first derive features static features (MFCC, chromagram) or proposed dynamic features. Two approaches are then studied in order to derive automatically the structure of a piece of music. The sequence approach considers ...

A supervised learning approach to ambience extraction from onechannel audio signals is presented. The extracted ambient signals are applied for the blind upmixing of musical audio recordings to surround sound formats. The input signal is processed by means of short-term spectral attenuation. The spectral weights are computed using a low-level feature extraction process and a neural network regr...

A new algorithm for embedding a digital watermark into an audio signal is proposed. It uses spread spectrum theory to generate a watermark resistant to different removal attempts and a psychoacoustic auditory model to shape and embed the watermark into the audio signal while retaining the signal’s perceptual quality. Recovery is performed without knowledge of the original audio signal. A softwa...

Watermarking an audio signal is a very crucial thing. So a new watermarking technique Empirical Mode Decomposition (EMD) is introduced. The audio signal is first split into frames and each one is then decomposed by EMD to get intrinsic periodic components known as Intrinsic Mode Functions (IMFs). The combination of watermark and synchronization code are embedded into the last IMF, which is most...

Audio compression is the lossy compression technique of converting audio signal into an efficiently encoded bitstream that can be decoded to produce a close approximation of the original signal. For the purpose of improving the coding this work attempts to combine psychoacoustic model for perceptual evaluation of audio quality in BS.1387 with perceptual audio coder. The implementation of this n...