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CHAPTER Regular Expressions, Text Normalization, Edit Distance

Speech and Language Processing. Daniel Jurafsky & James H. Martin. Copyright 2021. Allrights reserved. Draft of December 29, ,TextNormalization, Edit DistanceUser: I am : DO YOU THINK COMING HERE WILL HELP YOU NOT TO BE UNHAPPYUser: I need some help, that much seems : WHAT WOULD IT MEAN TO YOU IF YOU GOT SOME HELPUser: Perhaps I could learn to get along with my : TELL ME MORE ABOUT YOUR FAMILYUser: My mother takes care of : WHO ELSE IN YOU FAMILY TAKES CARE OF YOUUser: My : YOUR FATHERUser: You are like my father in some (1966)The dialogue above is fromELIZA, an early natural language processing systemELIZA that could carry on a limited conversation with a user by imitating the responses ofa Rogerian psychotherapist (Weizenbaum, 1966). ELIZA is a surprisingly simpleprogram that uses pattern matching to recognize phrases like I need X and translatethem into suitable outputs like What would it mean to you if you got X?

tokenization text, the task of tokenization. English words are often separated from each other by whitespace, but whitespace is not always sufficient. New York and rock ’n’ roll are sometimes treated as large words despite the fact that they contain spaces, while sometimes we’ll need to separate I’m into the two words I and am.

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