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Bigrams are groups of two written letters, two syllables, or two words, and are very commonly used as the basis for simple statistical analysis of text; one of the most successful language models for speech recognition (Collins, 1996). They are a special case of N-gram. Gappy bigrams or skipping bigrams are word pairs which allow gaps (perhaps avoiding connecting words, or allowing some simulation of dependencies, as in a dependency grammar). Head word bigrams are gappy bigrams with an explicit dependency relationship. The term is also used in cryptography, where bigram frequency attacks have sometimes been used to attempt to solve cryptograms. See frequency analysis. Bigrams help provide the conditional probability of a word given the preceding word, when Bayes' theorem is applied: That is, the probability of a word given the preceding word is equal to the probability of their bigram, or the co-occurrence of the two words , divided by the probability of the preceding word.
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