Speech and Language Processing: An Introduction to Natural by Daniel Jurafsky, James H. Martin

By Daniel Jurafsky, James H. Martin

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Extra resources for Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition

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Second edition. Thompson, K. (1968). Regular expression search algorithm. Communications of the ACM, 11(6), 419–422. Turing, A. M. (1936). On computable numbers, with an application to the Entscheidungsproblem. Proceedings of the London Mathematical Society, 42, 230–265. Read to the Society in 1936, but published in 1937. Correction in volume 43, 544–546. van Santen, J. P. H. and Sproat, R. (1998). Methods and tools. In Sproat, R. ), Multilingual Text-To-Speech Synthesis: The Bell Labs Approach, pp.

So for example the word fox consists of a single morpheme (the morpheme fox) while the word cats consists of two: the morpheme cat and the morpheme -s. As this example suggests, it is often useful to distinguish two broad classes of morphemes: stems and affixes. The exact details of the distinction vary from language to language, but intuitively, the stem is the “main” morpheme of the word, supplying the main meaning, while the affixes add “additional” meanings of various kinds. Affixes are further divided into prefixes, suffixes, infixes, and circumfixes.

0/ is a regular language 2. ∀a ∈ Σ ∪ ε, {a} is a regular language 3. If L1 and L2 are regular languages, then so are: (a) L1 · L2 = {xy | x ∈ L1 , y ∈ L2 }, the concatenation of L1 and L2 (b) L1 ∪ L2 , the union or disjunction of L1 and L2 (c) L∗1 , the Kleene closure of L1 Only languages which meet the above properties are regular languages. Since the regular languages are the languages characterizable by regular expressions, all the regular expression operators introduced in this chapter (except memory) can be implemented by the three operations which define regular languages: concatenation, disjunction/union (also called “|”), and Kleene closure.

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