In contrast to image compression, lossless audio compression algorithms are not widely used, except perhaps for certain professional applications.
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 samples 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.
Most lossy audio compression algorithms are based on simple transforms like the [discrete cosine transform]? (DCT), that convert sampled waveforms into their component frequencies. Some modern algorithms use wavelets?, but it is still not certain if such algorithms will work significantly better than those based on DCT. Some algorithms try to merge the two approaches.
Most algorithms don't try to minimize mathematical error, but instead maximize subjective human feeling of fidelity. As the human ear cannot analyze all components of an incoming sound, a file can be considerably modified without changing the subjective experience of a listener. For example information about very low and very high frequencies, which are almost inaudible to humans, is often reduced or even totally removed. Similarly, frequencies which are "masked" by other frequencies due to the nature of the human cochlea?, are represented with decreased accuracy. Such a model of the human ear is often called a psychoacoustic model.
Due to the nature of lossy algorithms, audio quality suffers when a file is decompressed and recompressed. This makes lossily-compressed files less than ideal for professional applications, such as sound editing and multitrack recording.
Some examples of popular audio codecs are:
Other examples can be found on the codec page.
See also: psychoacoustics, audio file format, audio signal processing, data compression, video file formats, [audio storage]?, codec, digital signal processing, speech coding
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