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There is one count that puts the English vocabulary at about 1 million words—but that count presumably includes words such as Latin species names, prefixed and suffixed words, scientific terminology, jargon, foreign words of extremely limited English use and technical acronyms. [42] [43] [44] Urdu: 264,000
Nonetheless, it is essential in some cases to explicitly model the probability of out-of-vocabulary words by introducing a special token (e.g. <unk>) into the vocabulary. Out-of-vocabulary words in the corpus are effectively replaced with this special <unk> token before n-grams counts are cumulated. With this option, it is possible to estimate ...
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 linguistics, lexical similarity is a measure of the degree to which the word sets of two given languages are similar. A lexical similarity of 1 (or 100%) would mean a total overlap between vocabularies, whereas 0 means there are no common words. There are different ways to define the lexical similarity and the results vary accordingly.
Even in English, the deviations from the ideal Zipf's law become more apparent as one examines large collections of texts. Analysis of a corpus of 30,000 English texts showed that only about 15% of the texts in it have a good fit to Zipf's law. Slight changes in the definition of Zipf's law can increase this percentage up to close to 50%. [45]
In particular, words relating to technology, such as "blog," which, in 2014, was #7665 in frequency [7] in the Corpus of Contemporary American English, [8] was first attested to in 1999, [9] [10] [11] and does not appear in any of these three lists. The Teachers Word Book of 30,000 words (Thorndike and Lorge, 1944)
Lexical diversity is one aspect of 'lexical richness' and refers to the ratio of different unique word stems (types) to the total number of words ().The term is used in applied linguistics and is quantitatively calculated using numerous different measures including Type-Token Ratio (TTR), vocd, [1] and the measure of textual lexical diversity (MTLD).
The Coleman–Liau index is a readability test designed by Meri Coleman and T. L. Liau to gauge the understandability of a text. Like the Flesch–Kincaid Grade Level, Gunning fog index, SMOG index, and Automated Readability Index, its output approximates the U.S. grade level thought necessary to comprehend the text.