Audio compression is the technology of converting audio signal into an efficiently encoded representation that can later be decoded to engender a close approximation of the pristine signal. In this work we are investigating implementation of psychoacoustics utilizing different wavelets to compress high quality audio signal and maintaining transparent quality at low bit rates Most psychoacoustic...

Acoustic data transmission is a technique which embeds data in a sound wave imperceptibly and detects it at a receiver. The data are embedded in an original audio signal and transmitted through the air by playing back the data-embedded audio using a loudspeaker. At the receiver, the data are extracted from the received audio signal captured by a microphone. In our previous work, we proposed an ...

In this paper, we propose a new combined harmonic-wavelet representation for audio where a harmonic analysis-synthesis scheme is used, rst, to approximate each audio frame as a sum of several sinusoids. Then, the di erence between the original signal and the reconstructed harmonic signal is analyzed using a wavelet ltering scheme. After each step (harmonic analysis & wavelet ltering), parameter...

Classification systems of the audio signals are used for analysis of the input signal and then were used to extract the different characteristics or features of the audio signal. Classification of audio signal is used to draw some sensory and physical characteristics like voice and is used to determine their characteristics. Extraction algorithms can be used vastly, depending on the field of cl...

Aiming for high-level intentional control of audio feedback, though microphones, loudspeakers and digital signal processing, we present a system adapting toward chosen sonic features. Users control the system by selecting and changing feature objectives in real-time. The system has a second-order structure in which the internal signal processing algorithms are developed according to an evolutio...

Forensic audio recordings may contain undesired noise that can impair source identification, speech recognition, and other audio processing requirements. In this paper several custom analysis/synthesis algorithms are presented based on a time-varying spectral representation of the noisy signal. The enhancement process adapts to the instantaneous signal behavior and alters the noisy signal so th...

Just about all the newest living room audio-video electronics and PC multimedia products being designed today will incorporate some form of compressed digitized-audio processing capability. Audio compression reduces the bit rate required to represent an analog audio signal while maintaining the perceived audio quality. Discarding inaudible data reduces the storage, transmission and compute requ...

Audio forensics applies the tools and techniques of audio engineering and digital signal processing to study audio data as part of a legal proceeding or an official investigation of some kind. This chapter summarizes the principal audio forensic tasks, including authentication, enhancement, and interpretation. The chapter explains the relevant procedural and historical background, presents seve...

Structured audio uses a high level representation of a signal to produce audio output. When it was first introduced in 1998, creating a structured audio representation from an audio signal was beyond the state-of-the-art. Inspired by object coding and structured audio, we present a system to reproduce audio using Expressive MIDI, high-level parameters being used to represent pitch expression fr...

In this article echo state networks, a special form of recurrent neural networks, are discussed in the area of nonlinear audio signal processing. Echo state networks are a novel approach in recurrent neural networks with a very easy (linear) training algorithm. Signal processing examples in nonlinear system identification (valve distortion, clipping), inverse modeling (quality enhancement) and ...