Lossless compression of digital audio

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004

In this paper, we propose an efficient lossless coding algorithm that not only handles both PCM format data and IEEE floatingpoint format data, but also provides end users with random access property. In the worst-case scenario, where the proposed algorithm was applied to artificially generated full 32-bit floating-point sound files with 48-or 96-kHz sampling frequencies, an average compression rate of more than 1.5 and 1.7, respectively, was still achieved, which is much better than the average compression rate of less than 1.1 achieved by general purpose lossless coding algorithm gzip. Moreover, input sound files with samples' magnitude out-of-range can also be perfectly reconstructed by our algorithm.

Indonesian Journal of Electrical Engineering and Computer Science, 2017

Audio compression is a method of reducing the space demand and aid transmission of the source file which then can be categorized by lossy and lossless compression. Lossless audio compression was considered to be a luxury previously due to the limited storage space. However, as storage technology progresses, lossless audio files can be seen as the only plausible choice for those seeking the ultimate audio quality experience. There are a lot of commonly used lossless codecs are FLAC, Wavpack, ALAC, Monkey Audio, True Audio, etc. The IEEE Standard for Advanced Audio Coding (IEEE 1857.2) is a new standard approved by IEEE in 2013 that covers both lossy and lossless audio compression tools. A lot of research has been done on this standard, but this paper will focus more on whether the IEEE 1857.2 lossless audio codec to be a viable alternative to other existing codecs in its current state. Therefore, the objective of this paper is to investigate the codec’s operation as initial measureme...

2004

This thesis studies lossless audio compression. In the domain of lossless compression, research takes place on two broad development sections, signal modeling and coding algorithm. The former is concerned with the understanding of the source signal, while coding is the more tightly specified task of efficiently representing a single symbol as a code. The focus of this thesis is the evaluation and the development of signal modeling techniques for lossless compression. Related with the modeling method used to decorrelate a signal, the data compression schemes are generally divided in two categories, predictive modeling and transform-based modeling. In the thesis, all two categories are investigated in depth and handled from the lossless viewpoint. The first contribution of the thesis is an exploration of the general audio compression systems including the lossy compression system. In predictive modeling, the structures of various linear prediction filters are introduced by presenting the fundamental autoregressive modeling. The prediction filters including the approaches to the nonstationary signal modeling and to the adaptive linear prediction filters are explored and evaluated by testing within a prototypical lossless audio compression system. For transform modeling, two well-known subband transform coding methods, Laplacian pyramid and subband coding scheme, are first described, and then the design methods of perfect reconstruction multirate filter banks are studied. Concerning with the modulated lapped orthogonal transform, the efficiency of linear prediction from subband and from fullband is formally compared and empirically examined. Wavelet transform is in depth studied from the various viewpoints in order to find the theoretical relationship between the wavelet and the multirate filter banks. Theoretical and practical aspects of reversible transforms are discussed by introducing the S-transform, S+P transform, and RTS transform. The lifting method is examined as a means to realize the biorthogonal wavelets. Integer lifting scheme with rounding-off method is investigated to construct reversible version of wavelet transforms and its performance is validated by applying to lossless audio compression. Finally, some of the more important results presented in this thesis are summarized with the suggesting directions for future research.

2010

This paper presents a theory of lossless digital compression. Quality of voice signal is not important for voice communication. In hearing music high quality music is always recommended. For this emphasis is given on the quality of speech signal. To save more music it is needed to save them consuming smaller memory space. In proposed compression 8-bit PCM/PCM speech signal is compressed. When values of samples are varying they are kept same. When they are not varying the number of samples containing same value is saved. After compression the signal is also an 8bit PCM/PCM. MPEG-4 ALS is applied in this compressed PCM signal for better compression.

1996

This tutorial covers the theory behind MPEG/audio compression. This algorithm was developed by the Motion Picture Experts Group (MPEG), as an International Organization for Standardization (ISO) standard for the high fidelity compression of digital audio. The MPEG/audio compression standard is one part of a multiple part standard that addresses the compression of video (11172-2), the compression of audio (11172-3), and the synchronization of the audio, video, and related data streams (11172-1) to an aggregate bit rate of about 1.5 Mbits/sec. The MPEG/audio standard also can be used for audio-only applications to compress high fidelity audio data at much lower bit rates. While the MPEG/audio compression algorithm is lossy, often it can provide "transparent", perceptually lossless, compression even with compression factors of 6-to-1 or more. The algorithm works by exploiting the perceptual properties of the human auditory system. This paper also will cover the basics of psychoacoustic modeling and the methods used by the MPEG/audio algorithm to compress audio data with least perceptible degradation. • MPEG/audio offers a choice of three independent layers of compression. This provides a wide range of tradeoffs between codec complexity and compressed audio quality: Layer I is the simplest and is best suited for bit rates above 128 kbits/sec per channel. For example, Philips' Digital Compact Cassette (DCC) [5] uses Layer I compression at 192 kbits/s per channel. Layer II has an intermediate complexity and is targeted for bit rates around 128 kbits/s per channel. Possible applications for this layer include the coding of audio for Digital Audio Broadcasting (DAB ®) [6] , for the storage of synchronized video-and-audio sequences on CD-ROM, and the full motion extension of CD-interactive, Video CD. Layer III is the most complex but offers the best audio quality, particularly for bit rates around 64 kbits/s per channel. This layer is well suited for audio transmission over ISDN. All three layers are simple enough to allow single-chip, real-time decoder implementations.

2010

The field of speech compression has advanced rapidly due to cost-effective digital technology and diverse commercial applications. In voice communication a real-time system should be considered. It is not still possible to compress signals without facing any loss in real-time system. This paper presents a theory of loss-less digital compression for saving high quality speech signals. Emphasis is given on the quality of speech signal. In hearing music high quality music is always needed, consuming smaller memory space. In this compression 8-bit PCM/PCM speech signal is compressed. When values of samples are varying they are kept same. When they are not varying the number of samples containing same value is saved. After compression the signal is also an 8-bit PCM/PCM but expansion is needed before hearing it. This technique may also be used in real-time systems.

Sigma delta modulation is a popular technique for high-resolution analog-to-digital conversion and digital-toanalog-conversion. It has been considered as a new format for recording and storage of audio signals. To reduce the storage capacity, a lossless compression scheme can be applied. However, this scheme offers less than 3:1 compression. This may not be sufficient for storage on media such as a Digital Versatile Disk (DVD). We propose a scheme based on a technique known as bit-grouping. Errors are introduced in the compression, but they are confined to frequencies outside the audible range. Our studies indicate that bit-grouping allows one to achieve greater than 4:1 compression.

This paper discusses the design and implementation of a scalable audio compression scheme that scales up from lossy to lossless compression. Scalable audio compression has been of interest in the audio compression community for some time, with the most obvious attempt at obtaining a solution coming in the form of the MPEG-4 standard [1]. At the same time the increase in bit rates in both mobile communications [2] and the internet's broadband technology means that audio compression algorithms with higher bit rates than currently used, such as MPEG's mp3 [1], can be employed to obtain higher quality. However, the new increased data rates are not necessarily constant, this is especially the case when considering the internet. As such, scalable schemes that can scale to lossless compression have become rather interesting from an application point of view. The scheme presented in this paper achieves lossless compression that is comparable with the state of the art whilst maintain...

Indonesian Journal of Electrical Engineering and Computer Science, 2018

In recent years, multichannel audio systems are widely used in modern sound devices as it can provide more realistic and engaging experience to the listener. This paper focuses on the performance evaluation of three lossy, i.e. AAC, Ogg Vorbis, and Opus, and three lossless compression, i.e. FLAC, TrueAudio, and WavPack, for multichannel audio signals, including stereo, 5.1 and 7.1 channels. Experiments were conducted on the same three audio files but with different channel configurations. The performance of each encoder was evaluated based on its encoding time (averaged over 100 times), data reduction, and audio quality. Usually, there is always a trade-off between the three metrics. To simplify the evaluation, a new integrated performance metric was proposed that combines all the three performance metrics. Using the new measure, FLAC was found to be the best lossless compression, while Ogg Vorbis and Opus were found to be the best for lossy compression depends on the channel configuration. This result could be used in determining the proper audio format for multichannel audio systems.

IEEE Transactions on Speech and Audio Processing, 2003

To design, implement and test a lossless compression/decompression tool for digital audio. This technique is used to reduce the digital data that has to be transmitted over the communications channel. The implementation can be done on the FPGA or DSP boards.