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by: Gretchen Schmidt


Gretchen Schmidt
GPA 3.6


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Class Notes
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This 3 page Class Notes was uploaded by Gretchen Schmidt on Saturday September 26, 2015. The Class Notes belongs to LING 120 at Iowa State University taught by Staff in Fall. Since its upload, it has received 38 views. For similar materials see /class/214431/ling-120-iowa-state-university in Linguistics at Iowa State University.




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Date Created: 09/26/15
LING 120 Computers and Language Topic 2 A Little Bit of History Reading Ch 1 o What is the difference bw data processing computer language processing natural language processing and computational linguistics What does it take to do natural language processing What types of knowledge is needed 0 Phonetics Phonology o Morphology o Syntax o Semantics o Pragmatics Discourse Problem 0 Many di erent ways to say the same thing I John ate a frog I Afrog was eaten by John I A frog was eaten I It was John who ate the frog I The one who ate the frog was John I What was eaten by John was a frog I What John ate was a frog I M y friend John ingested an aquatic leaping anuran amphibian I 0 Many di erent ways to interpret the same thing Do you have a pen gt Do you possess an implementfor writing or drawing with ink or a similarfluid Do you possess a small enclosure for animals Do you possess a small place of confinement or storage Do you possess a protected dock or slip for a submarine Do you possess a female swan Do you possess a penitentiary Do you habitually eat an implement for writing or drawing with ink or a similar uid Do you habitually eat a small enclosure for animals Extracting the intended meaning and producing the appropriate structure from a meaning representation ef ciently is a central problem of computational linguistics What is thinking What is understanding Turing vs Searle Can machines think and does that matter 0 ELIZA 1 l httpWWW im nhn I httpwwwaiijssielizaelizahtml 0 Today s dialogue systems Historical Threads 0 Computational Linguistics Linguistics 0 Natural Language Processing Computer Science 0 Speech Processing Electrical Engineering 0 Computational Psycholinguistics Cognitive SciencePsychology Early Days l940sl950s 0 Finite State AutomataRegular Languages Turing Shannon Kleene o Context Free Grammars Chomsky o Noisy Channel Models Shannon Two Camps 19571970 0 Symbolic I Generative Transformational Grammar Ha1ris Chomsky I Symbolic AI McCarthy Minsky Shannon Rochester Newell Simon 0 Stochastic Bledsoe Browning Mosteller Wallace 0 Emergence of first computer corpora Brown Corpus and machinereadable dictionaries DOC Four Paradigms 19701983 0 Speech recognition IBM Carnegie Mellon stochastic HMM noisy channel models 0 De nite Clause Grammars in Prolog Pereira Warren Lexical Functional Grammar LFG Kay Bresnan Kaplan logic based 0 Natural Language Understanding N LU focus on meaning I SHRDLU httn39 hci stanfnrd edn J 39 J39 I Schank s scripts focus on understanding text and stories 0 Discourse Modeling I Centering Theory Grosz focuses on anaphor resolution Empiricism NLG Finite State Models 19831993 0 Return of nite state models 0 Return of probabilistic approaches speech recognition partofspeech tagging ambiguity resolution 0 Natural Language Generation NLG symbolic Together Again l994present 0 Statistical Machine Translation 0 Probabilistic Parsing 0 Statistical NLG 0 Extended use of machine learning techniques 0 Information retrieval and text categorization


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