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Word count is commonly used by translators to determine the price of a translation job. Word counts may also be used to calculate measures of readability and to measure typing and reading speeds (usually in words per minute). When converting character counts to words, a measure of 5 or 6 characters to a word is generally used for English. [1]
In computing, a word is any processor design's natural unit of data. A word is a fixed-sized datum handled as a unit by the instruction set or the hardware of the processor. The number of bits or digits [a] in a word (the word size, word width, or word length) is an important characteristic of any specific processor design or computer architecture.
In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other.
For a fixed length n, the Hamming distance is a metric on the set of the words of length n (also known as a Hamming space), as it fulfills the conditions of non-negativity, symmetry, the Hamming distance of two words is 0 if and only if the two words are identical, and it satisfies the triangle inequality as well: [2] Indeed, if we fix three words a, b and c, then whenever there is a ...
The electronic computer word length of 36-bits was chosen, in part, to match its precision. Starting in the 1960s, but especially the 1970s, the introduction of 7-bit ASCII and 8-bit EBCDIC led to the move to machines using 8-bit bytes, with word sizes that were multiples of 8, notably the 32-bit IBM System/360 mainframe and Digital Equipment ...
In many East Asian languages, such as Chinese, Tibetan, and Vietnamese, each morpheme (word or word piece) consists of a single syllable; a word of English being often translated to a compound of two such syllables. The rank-frequency table for those morphemes deviates significantly from the ideal Zipf law, at both ends of the range.
When the data word is divided into 16-bit blocks, two 16-bit sums result and are combined into a 32-bit Fletcher checksum. Usually, the second sum will be multiplied by 2 16 and added to the simple checksum, effectively stacking the sums side-by-side in a 32-bit word with the simple checksum at the least significant end. This algorithm is then ...
The formula was inspired by Rudolf Flesch's Flesch–Kincaid readability test which used word-length to determine how difficult a word was for readers to understand. [1] Edgar Dale and Jeanne Chall instead used a list of 769 words that 80% of fourth-grade students were familiar with, such as "no", "yes", and other such very basic words to ...