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G.711.1
G.711 is a narrowband audio codec originally designed for use in telephony that provides toll-quality audio at 64 kbit/s. G.711 passes audio signals in the range of 300–3400 Hz and samples them at the rate of 8,000 samples per second, with the tolerance on that rate of 50 parts per million (ppm). Non-uniform (logarithmic) quantization with 8 bits is used to represent each sample, resulting in a 64 kbit/s bit rate. There are two slightly different versions: μ-law, which is used primarily in North America and Japan, and A-law, which is in use in most other countries outside North America. G.711 is an ITU-T standard (Recommendation) for audio companding, titled Pulse code modulation (PCM) of voice frequencies released for use in 1972. It is a required standard in many technologies, such as in the H.320 and H.323 standards. It can also be used for fax communication over IP networks (as defined in T.38 specification). Two enhancements to G.711 have been published: ...
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List Of Codecs
The following is a list of compression formats and related codecs. Audio compression formats Non-compression * Linear pulse-code modulation (LPCM, generally only described as PCM) is the format for uncompressed audio in media files and it is also the standard for CD-DA; note that in computers, LPCM is usually stored in container formats such as WAV, AIFF, or AU, or as raw audio format, although not technically necessary. ** FFmpeg * Pulse-density modulation (PDM) ** Direct Stream Digital (DSD) is standard for Super Audio CD *** foobar2000 Super Audio CD Decoder (based on MPEG-4 DST reference decoder) *** FFmpeg (based on dsd2pcm) * Pulse-amplitude modulation (PAM) Lossless compression * Actively used ** Most popular *** Free Lossless Audio Codec (FLAC) **** libFLAC **** FFmpeg *** Apple Lossless Audio Codec (ALAC) **** Apple QuickTime **** libalac **** FFmpeg **** Apple Music *** Monkey's Audio (APE) **** Monkey's Audio SDK **** FFmpeg (decoder only) *** OptimFROG (OFR) *** T ...
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Comparison Of Audio Coding Formats
The following tables compare general and technical information for a variety of audio coding formats. For listening tests comparing the perceived audio quality of audio formats and codecs, see the article Codec listening test. General information Notes # The 'Music' category is merely a guideline on commercialized uses of a particular format, not a technical assessment of its capabilities. (For example, in terms of marketshare, MP3 and AAC dominate the personal audio market, though many other formats are comparably well suited to fill this role from a purely technical standpoint.) # First public release date is first of either specification publishing or source releasing, or in the case of closed-specification, closed-source codecs, is the date of first binary releasing. Many developing codecs have pre-releases consisting of pre-1.0 versions and perhaps 1.0 release candidates (RCs), although 1.0 may not necessarily be the release version. # Latest stable version is that of ...
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Logarithmic Scale
A logarithmic scale (or log scale) is a way of displaying numerical data over a very wide range of values in a compact way—typically the largest numbers in the data are hundreds or even thousands of times larger than the smallest numbers. Such a scale is nonlinear: the numbers 10 and 20, and 60 and 70, are not the same distance apart on a log scale. Rather, the numbers 10 and 100, and 60 and 600 are equally spaced. Thus moving a unit of distance along the scale means the number has been ''multiplied'' by 10 (or some other fixed factor). Often exponential growth curves are displayed on a log scale, otherwise they would increase too quickly to fit within a small graph. Another way to think about it is that the ''number of digits'' of the data grows at a constant rate. For example, the numbers 10, 100, 1000, and 10000 are equally spaced on a log scale, because their numbers of digits is going up by 1 each time: 2, 3, 4, and 5 digits. In this way, adding two digits ''multiplies'' the ...
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MDCT
The modified discrete cosine transform (MDCT) is a transform based on the type-IV discrete cosine transform (DCT-IV), with the additional property of being lapped: it is designed to be performed on consecutive blocks of a larger dataset, where subsequent blocks are overlapped so that the last half of one block coincides with the first half of the next block. This overlapping, in addition to the energy-compaction qualities of the DCT, makes the MDCT especially attractive for signal compression applications, since it helps to avoid artifacts stemming from the block boundaries. As a result of these advantages, the MDCT is the most widely used lossy compression technique in audio data compression. It is employed in most modern audio coding standards, including MP3, Dolby Digital (AC-3), Vorbis (Ogg), Windows Media Audio (WMA), ATRAC, Cook, Advanced Audio Coding (AAC), High-Definition Coding (HDC), LDAC, Dolby AC-4, and MPEG-H 3D Audio, as well as speech coding standards such as AAC- ...
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Wideband
In communications, a system is wideband when the message bandwidth significantly exceeds the coherence bandwidth of the Channel (communications), channel. Some communication links have such a high Bit rate, data rate that they are forced to use a wide bandwidth Bandwidth commonly refers to: * Bandwidth (signal processing) or ''analog bandwidth'', ''frequency bandwidth'', or ''radio bandwidth'', a measure of the width of a frequency range * Bandwidth (computing), the rate of data transfer, bit rate or thr ...; other links may have relatively low data rates, but deliberately use a wider bandwidth than "necessary" for that data rate in order to gain other advantages; see ''spread spectrum''. A wideband Antenna (radio), antenna is one with approximately or exactly the same operating characteristics over a very wide Passband. It is distinguished from broadband antennas, where the passband is large, but the antenna gain and/or radiation pattern need not stay the same over the passband ...
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Clock Recovery
In serial communication of digital data, clock recovery is the process of extracting timing information from a serial data stream itself, allowing the timing of the data in the stream to be accurately determined without separate clock information. It is widely used in data communications; the similar concept used in analog systems like color television is known as carrier recovery. Basic concept Serial data is normally sent as a series of pulses with well-defined timing constraints. This presents a problem for the receiving side; if their own local clock is not precisely synchronized with the transmitter, they may sample the signal at the wrong time and thereby decode the signal incorrectly. This can be addressed with extremely accurate and stable clocks, like atomic clocks, but these are expensive and complex. More common low-cost clock systems, like quartz oscillators, are accurate enough for this task over short periods of time, but over a period of minutes or hours the drift in ...
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Least Significant Bit
In computing, bit numbering is the convention used to identify the bit positions in a binary number. Bit significance and indexing In computing, the least significant bit (LSB) is the bit position in a binary integer representing the binary 1s place of the integer. Similarly, the most significant bit (MSB) represents the highest-order place of the binary integer. The LSB is sometimes referred to as the ''low-order bit'' or ''right-most bit'', due to the convention in positional notation of writing less significant digits further to the right. The MSB is similarly referred to as the ''high-order bit'' or ''left-most bit''. In both cases, the LSB and MSB correlate directly to the least significant digit and most significant digit of a decimal integer. Bit indexing correlates to the positional notation of the value in base 2. For this reason, bit index is not affected by how the value is stored on the device, such as the value's byte order. Rather, it is a property of the numeri ...
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Exponent
Exponentiation is a mathematical operation, written as , involving two numbers, the '' base'' and the ''exponent'' or ''power'' , and pronounced as " (raised) to the (power of) ". When is a positive integer, exponentiation corresponds to repeated multiplication of the base: that is, is the product of multiplying bases: b^n = \underbrace_. The exponent is usually shown as a superscript to the right of the base. In that case, is called "''b'' raised to the ''n''th power", "''b'' (raised) to the power of ''n''", "the ''n''th power of ''b''", "''b'' to the ''n''th power", or most briefly as "''b'' to the ''n''th". Starting from the basic fact stated above that, for any positive integer n, b^n is n occurrences of b all multiplied by each other, several other properties of exponentiation directly follow. In particular: \begin b^ & = \underbrace_ \\ ex& = \underbrace_ \times \underbrace_ \\ ex& = b^n \times b^m \end In other words, when multiplying a base raised to one exp ...
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Significand
The significand (also mantissa or coefficient, sometimes also argument, or ambiguously fraction or characteristic) is part of a number in scientific notation or in floating-point representation, consisting of its significant digits. Depending on the interpretation of the exponent, the significand may represent an integer or a fraction. Example The number 123.45 can be represented as a decimal floating-point number with the integer 12345 as the significand and a 10−2 power term, also called characteristics, where −2 is the exponent (and 10 is the base). Its value is given by the following arithmetic: : 123.45 = 12345 × 10−2. The same value can also be represented in normalized form with 1.2345 as the fractional coefficient, and +2 as the exponent (and 10 as the base): : 123.45 = 1.2345 × 10+2. Schmid, however, called this representation with a significand ranging between 1.0 and 10 a modified normalized form. For base 2, this 1.xxxx form is also called a normalized ...
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Floating-point Arithmetic
In computing, floating-point arithmetic (FP) is arithmetic that represents real numbers approximately, using an integer with a fixed precision, called the significand, scaled by an integer exponent of a fixed base. For example, 12.345 can be represented as a base-ten floating-point number: 12.345 = \underbrace_\text \times \underbrace_\text\!\!\!\!\!\!^ In practice, most floating-point systems use base two, though base ten (decimal floating point) is also common. The term ''floating point'' refers to the fact that the number's radix point can "float" anywhere to the left, right, or between the significant digits of the number. This position is indicated by the exponent, so floating point can be considered a form of scientific notation. A floating-point system can be used to represent, with a fixed number of digits, numbers of very different orders of magnitude — such as the number of meters between galaxies or between protons in an atom. For this reason, floating-poin ...
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Most Significant Bit
In computing, bit numbering is the convention used to identify the bit positions in a binary number. Bit significance and indexing In computing, the least significant bit (LSB) is the bit position in a binary integer representing the binary 1s place of the integer. Similarly, the most significant bit (MSB) represents the highest-order place of the binary integer. The LSB is sometimes referred to as the ''low-order bit'' or ''right-most bit'', due to the convention in positional notation of writing less significant digits further to the right. The MSB is similarly referred to as the ''high-order bit'' or ''left-most bit''. In both cases, the LSB and MSB correlate directly to the least significant digit and most significant digit of a decimal integer. Bit indexing correlates to the positional notation of the value in base 2. For this reason, bit index is not affected by how the value is stored on the device, such as the value's byte order. Rather, it is a property of the numeri ...
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Signed Magnitude
In computing, signed number representations are required to encode negative numbers in binary number systems. In mathematics, negative numbers in any base are represented by prefixing them with a minus sign ("−"). However, in RAM or CPU registers, numbers are represented only as sequences of bits, without extra symbols. The four best-known methods of extending the binary numeral system to represent signed numbers are: sign–magnitude, ones' complement, two's complement, and offset binary. Some of the alternative methods use implicit instead of explicit signs, such as negative binary, using the base −2. Corresponding methods can be devised for other bases, whether positive, negative, fractional, or other elaborations on such themes. There is no definitive criterion by which any of the representations is universally superior. For integers, the representation used in most current computing devices is two's complement, although the Unisys ClearPath Dorado series mainframes u ...
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