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CSE467/567 Computational Linguistics Carl Alphonce Computer Science & Engineering University at Buffalo.

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Presentation on theme: "CSE467/567 Computational Linguistics Carl Alphonce Computer Science & Engineering University at Buffalo."— Presentation transcript:

1 CSE467/567 Computational Linguistics Carl Alphonce cse-467-alphonce@cse.buffalo.edu Computer Science & Engineering University at Buffalo

2 Fall 2006CSE 467/567 2 What is Computational Linguistics? The study of techniques for processing natural human language by computer. “computational techniques that process spoken and written language, as language” [Jurafsky & Martin, pg. 2] We will deal almost exclusively with written language.

3 Fall 2006CSE 467/567 3 Some applications – extant and envisioned spelling checkers grammar checkers natural language interfaces information extraction text summarization conversational agents machine translation

4 Fall 2006CSE 467/567 4 General problem areas information retrieval (finding sources) information extraction (extracting from sources) speech recognition natural language understanding inference (drawing conclusions) natural language generation speech synthesis

5 Fall 2006CSE 467/567 5 If only…

6 Fall 2006CSE 467/567 6 Levels of processing phonetics/phonology – sounds morphology – word structure syntax – sentence structure semantics – meaning pragmatics – goals of language use discourse – utterances in context

7 Fall 2006CSE 467/567 7 Basic models state machines – e.g. finite state automata and transducers formal rule systems – e.g. regular and context-free grammars logic – e.g. first-order logic, semantic networks probabilistic/statistical models

8 Fall 2006CSE 467/567 8 Basic algorithmic techniques state space search – searching through possible hypotheses – e.g. depth-first, best-first dynamic programming – solving problems by combining solutions to subproblems without recomputation by storing subproblem solutions in a table

9 Fall 2006CSE 467/567 9 Ambiguity – a pervasive problem An expression is ambiguous if it has two or more different possible interpretations. Ambiguity exists at every level of linguistic representation E.g. I made her duck (pg. 4) – I cooked waterfowl for her. – I cooked waterfowl belonging to her. – I created the (fake) duck she owns. – I caused her to quickly lower her head or body. – I waved my magic wand and turned her into undifferentiated waterfowl.


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