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A Tutorial on MPEG/Audio Compression
IEEE Multimedia, 1995This tutorial covers the theory behind MPEG/audio compression. While lossy, the algorithm can often provide "transparent", perceptually lossless compression, even with factors of 6-to-1 or more. It exploits the perceptual properties of the human auditory system. The article also covers the basics of psychoacoustic modeling and the methods the algorithm
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Advances in speech and audio compression
Proceedings of the IEEE, 1994Speech and audio compression has advanced rapidly in recent years spurred on by cost-effective digital technology and diverse commercial applications. Recent activity in speech compression is dominated by research and development of a family of techniques commonly described as code-excited linear prediction (CELP) coding.
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Lossy Audio Compression Identification
2018 26th European Signal Processing Conference (EUSIPCO), 2018We propose a system which can estimate from an audio recording that has previously undergone lossy compression the parameters used for the encoding, and therefore identify the corresponding lossy coding format. The system analyzes the audio signal and searches for the compression parameters and framing conditions which match those used for the encoding.
Bongjun Kim, Zafar Rafii
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Methods for identifying traces of compression in audio
2013 1st International Conference on Communications, Signal Processing, and their Applications (ICCSPA), 2013Compression history of an audio may reveal very useful information when traces of tampering has to be investigated or quality of an audio has to be evaluated. Motivated by this, we introduce two methods that can discriminate between single and double compressed audio and can identify compression codec and bit rate of an audio. The first method utilizes
Uzun, E., Hicsonmez, S., Sencar, H.T.
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Audio Compression: Technology and Applications
AT&T Technical Journal, 1995Recent algorithms for perceptual audio coding have provided the capability of compressing compact disk (CD)-stereo audio material (at 1,406 kbits/s) into rates approximating 128 kbits/s. This capability has enabled the development of several new classes of applications in audio transmission, broadcasting, and storage.
Nikil S. Jayant, Edward Y. Chen
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Lossy Audio Compression via Compressed Sensing
2010 Data Compression Conference, 2010We propose a Compressed Sensing application to audio signals and analyze its audio perceptual quality with PEAQ.
Rubem J. V. de Medeiros +2 more
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Generalized Lempel–Ziv Compression for Audio
IEEE Transactions on Audio, Speech and Language Processing, 2005We introduce a novel compression paradigm to generalize a class of Lempel-Ziv algorithms for lossy compression of multimedia. Based upon the fact that music, in particular electronically generated sound, has substantial level of repetitiveness within a single clip, we generalize the basic Lempel-Ziv compression algorithm to support representing a ...
Darko Kirovski, Zeph Landau
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Comparing audio compression using wavelets with other audio compression schemes
Engineering Solutions for the Next Millennium. 1999 IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.99TH8411), 2003Speech compression is the technology of converting human speech into an efficient encoded representation that can be decoded to produce a close approximation of the original signal. In this paper, we propose a new algorithm which compresses speech signals using a wavelet compression technique.
E.-B. Fgee, W.J. Phillips, W. Robertson
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Genre classification of compressed audio data
2008 IEEE 10th Workshop on Multimedia Signal Processing, 2008This paper deals with the musical genre classification problem, starting from a set of features extracted directly from MPEG-1 layer III compressed audio data. The automatic classification of compressed audio signals into a short hierarchy of musical genres is explored. More specifically, three feature sets for representing timbre, rhythmic content and
RIZZI, Antonello +3 more
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Quantized Perceptual Compressed Sensing for Audio Signal Compression
2015 Data Compression Conference, 2015Compressed Sensing (CS) has been widely used for multimedia processing to reduce the number of the measurements required to acquire signals that are spare or compressible sparse in some basis. CS provides good quality of the restored signal even when the signal is not completely sparse and even also at high compression ratio.
Hossam Mohamed Kasem +3 more
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