Audio data compression Guide, Meaning , Facts, Information and Description
Note: This article is about audio data compression, which reduces the data rate of digital audio signals. This should not be confused with audio level compression which reduces the dynamic range of audio signals, or companding, which uses both compression and complementary dynamic range expansion as a noise reduction techique for analog audio systems.
Audio compression is a form of data compression designed to reduce the size of audio data files. Audio compression algorithms are typically referred to as audio codecs. As with other specific forms of data compression, there exist many "lossless" and "lossy" algorithms to achieve the compression effect.
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2 Lossy compression 3 See also |
Compared with image compression, lossless compression algorithms are not nearly as widely used in audio compression. The primary users of lossless compression are audio engineers and those consumers who disdain the quality loss from lossy compression techniques such as Vorbis and MP3.
First, the vast majority of sound recordings are natural sounds, recorded from the real world, and such data doesn't compress well. In a similar manner, photos compress less efficiently with lossless methods than computer-generated images do. But worse, even computer generated sounds can contain very complicated waveforms that present a challenge to many compression algorithms. This is due to the nature of audio waveforms, which are generally difficult to simplify without a (necessarily lossy) conversion to frequency information, as performed by the human ear.
The second reason is that values of audio sampless change very quickly, so generic data compression algorithms don't work well for audio, and strings of consecutive bytes don't generally appear very often. However, convolution with the filter [-1 1] (that is, taking the first difference) tends to slightly whiten (decorrelate, make flat) the spectrum, thereby allowing traditional lossless compression at the encoder to do its job; integration at the decoder restores the original signal. More advanced codecs such as Shorten (SHN), FLAC and TTA uses linear prediction to estimate the spectrum of the signal. At the encoder, the estimator's inverse is used to whiten the signal by removing spectral peaks while the estimator is used to reconstruct the original signal at the decoder.
Some examples of popular lossless audio codecs:
In order to determine what information in an audio signal is perceptual irrelevant, most lossy compression algorithms use transforms such as the modified discrete cosine transform (MDCT) to convert sampled waveforms into a transform domain. Once transformed, typically into the frequency domain, component frequencies can be allocated bits according to how audible they are. Audibility of spectral components is determined by first calculating a masking threshold, below which it is estimated that sounds will be beyond the limits of human perception.
The masking threshold is calculated using the absolute threshold of hearing and the principles of simultaneous masking - the phenomenon wherein a signal is masked by another signal separated by frequency - and, in some cases, temporal masking - where a signal is masked by another signal separated by time. Equal-loudness contours may also be used to weight the perceptual importance of different components. Models of the human ear-brain combination incorporating such effects are often called psychoacoustic models or "psycho-models" for short.
Other types of lossy compressors, such as the linear predictive coding (LPC) used with speech, are source-based coders. These coders use a model of the sound's generator (such as the human vocal tract with LPC) to whiten the audio signal prior to quantization. LP may also be thought of as a basic perceptual coding technique; reconstruction of an audio signal using a linear predictor shapes the coder's quantization noise into the spectrum of the target signal, partially masking it.
Due to the nature of lossy algorithms, audio quality suffers when a file is decompressed and recompressed (generational losses). This makes lossy-compressed files unsuitable for audio engineering applications, such as sound editing and multitrack recording. However, they are very popular with end users (particularly MP3), as a megabyte can store about a minute's worth of music at adequate quality.
Some examples of popular audio codecs:
This is an Article on Audio data compression. Page Contains Information, Facts Details or Explanation Guide About Audio data compression Lossless compression
Examples
Lossless audio codecs have no quality issues, so the usabilty can be estimated by
See a comparison at [1] and a graph at [1]Lossy compression
As opposed to lossless compression, where information redundancy is reduced, most lossy compression reduces perceptual redundancy; sounds which are considered perceptually irrelevant are coded with decreased accuracy or not coded at all.Examples
Other examples can be found on the codec page.See also