1. 1 Introduction to Computational Linguistics Eleni Miltsakaki AUTH Spring 2006-Lecture 1

2. 2 Let’s introduce ourselves Course: Introduction to Computational Linguistics (Ling 2-342) Meeting times: Monday 11:00-14:00 Meeting place: here Prof: Eleni Miltsakaki BA Aristotle University -- English & American Lang. & Lit. MA University of Essex, UK -- Applied Linguistics PhD University of Pennsylvania, USA -- Theoretical and Computational Linguistics Students: ?

3. 3 What is Computational Linguistics? A discipline between Linguistics and Computer Science  Concerned with the computational aspects of human language processing  Has theoretical and applied components

4. 4 Theoretical CL Formal theories about the linguistic knowledge that a human needs for generating and understanding language Simulation of aspects of the human language faculty and their implementation as computer programs Overlaps and collaborates with Theoretical Linguistics, Computer Science, Psycholinguistics

5. 5 Applied CL Focuses on the practical outcome of modeling human language use –aka language engineering or human language technology Existing CL systems are far from achieving human ability but there are numerous possible and useful applications –Question/answering, summarization, translation, computer agents, educational applications etc

6. 6 Why is language so difficult for a computer? AMBIGUITY! Natural languages are massively ambiguous at all levels of processing (but humans don’t even notice…) To resolve ambiguity, humans employ not only a detailed knowledge of the language -- sounds, phonological rules, grammar, lexicon etc - - but also: –Detailed knowledge of the world (e.g. knowing that apples can have bruises but not smiles, or that snow falls but London does not). –The ability to follow a 'story', by connecting up sentences to form a continuous whole, inferring missing parts. –The ability to infer what a speaker meant, even if he/she did not actually say it. It is these factors that make NLs so difficult to process by computer -- but therefore so fascinating to study.

7. 7 Syntactic ambiguity I saw her duck The man closed the door with a bang The man closed the door with the black and white stripes

8. 8 Semantic ambiguity The man went over to the bank Mary loved Bill. Mary loved potato chips. Water runs down the hill. The road runs down the hill

9. 9 Phonological ambiguity Within words –Input, intake, income –Imput, intake, iNcome (N=ng) Across word boundaries –When playing football, watch the referee –When talking about other people, watch who’s listening –When catching a hard ball, wear gloves Homophones –I’m a writer and I write books –I’m a rider and I write books

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11. 11 Discourse Anaphora –London had snow yesterday It also had fog It fell to a depth of one meter It will continue cold today Speaker intentions –Can you swim –Can you tell me the time? –Can you pass the salt? Inference –You shouldn’t lend John any books. He never returns them.

12. 12 Language technology ALICE the chatbox –http://www.alicebot.org/http://www.alicebot.org/ Jabberwacky –http://www.jabberwacky.com/http://www.jabberwacky.com/ USC demo for learning Arabic –http://www.isi.edu/%7Ejmoore/Mankin/MankinTLWeb. movhttp://www.isi.edu/%7Ejmoore/Mankin/MankinTLWeb. mov