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The µ-law algorithm (pronounced mew-law) is a companding algorithm, primarily used in the digital telecommunication systems of North America and Japan. As with other companding algorithms, its purpose is to reduce the dynamic range of an audio signal. In the analog domain, this can increase the signal-to-noise ratio (SNR) achieved during transmission, and in the digital domain, it can reduce the quantization error (hence increasing signal to quantization noise ratio). These SNR increases can be traded instead for reduced bandwidth for equivalent SNR. It is similar to the A-law algorithm used in Europe.
Algorithm TypesThere are two forms of this algorithm - an analog version, and a quantized digital version. ContinuousFor a given input x, the equation for μ-law encoding is[1]
where μ = 255 (8 bits) in the North American and Japanese standards. μ-law expansion is then given by the inverse equation: The equations are culled from Cisco's Waveform Coding Techniques. DiscreteThis is defined in ITU-T Recommendation G.711 [2] G.711 is rather unclear about what the values at the limit of a range code up as. (e.g. whether +31 codes to 0xEF or 0xF0). However G.191 provides example C code for a μ-law encoder which gives the following encoding. Note the difference between the positive and negative ranges. e.g. the negative range corresponding to +30 to +1 is -31 to -2. This is accounted for by the use of a 1's complement (simple bit inversion) rather than 2's complement to convert a negative value to a positive value during encoding.
ImplementationThere are three ways of implementing a μ-law algorithm :
Usage JustificationThis encoding is used because speech has a wide dynamic range. In the analog world, when mixed with a relatively constant background noise source, the finer detail is lost. Given that the precision of the detail is compromised anyway, and assuming that the signal is to be perceived as audio by a human, one can take advantage of the fact that perceived intensity (loudness) is logarithmic[3] by compressing the signal using a logarithmic-response op-amp. In telco circuits, most of the noise is injected on the lines, thus after the compressor, the intended signal will be perceived as significantly louder than the static, compared to an un-compressed source. This became a common telco solution, and thus, prior to common digital usage, the μ-law specification was developed to define an inter-compatible standard. As the digital age dawned, it was noted that this pre-existing algorithm had the effect of significantly reducing the number of bits needed to encode recognizable human voice. Using μ-law, a sample could be effectively encoded in as few as 8 bits, a sample size that conveniently matched the symbol size of most standard computers. μ-law encoding effectively reduced the dynamic range of the signal, thereby increasing the coding efficiency while biasing the signal in a way that results in a signal-to-distortion ratio that is greater than that obtained by linear encoding for a given number of bits. This is an early form of perceptual audio encoding. The μ-law algorithm is also used in the .au format, which dates back at least to the SPARCstation 1 as the native method used by Sun's /dev/audio interface, widely used as a de facto standard for Unix sound. The .au format is also used in various common audio API's such as the classes in the This plot illustrates how μ-law concentrates sampling in the smaller (softer) values. The values of a μ-law byte 0-255 are the horizontal axis, the vertical axis is the 16 bit linear decoded value. This image was generated with the Sun Microsystems c routine g711.c commonly available on the Internet. Comparison with A-lawThe µ-law algorithm provides a slightly larger dynamic range than the A-law at the cost of worse proportional distortion for small signals. By convention, A-law is used for an international connection if at least one country uses it. This article contains material from the Federal Standard 1037C, which, as a work of the United States Government, is in the public domain. See also
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