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

Slides:



Advertisements
Similar presentations
The Attributive Clause The Attributive Clause Material 1: China is a big country that has about 5,000 years of history. Thats all (that) I know. Its.
Advertisements

Introduction to Computational Linguistics
Introduction to the theory of grammar
Introduction: The Chomskian Perspective on Language Study.
1 Language and kids Linguistics lecture #8 November 21, 2006.
1 Linguistics and translation theory Mark Shuttleworth Teaching Translation Swansea, 20 January 2006.
Linguistic Theory Lecture 8 Meaning and Grammar. A brief history In classical and traditional grammar not much distinction was made between grammar and.
LING 364: Introduction to Formal Semantics Lecture 26 April 20th.
Natural Language and Speech Processing Creation of computational models of the understanding and the generation of natural language. Different fields coming.
Introduction to Computational Linguistics Lecture 2.
1 Introduction to Linguistics II Ling 2-121C, group b Lecture 10 Eleni Miltsakaki AUTH Spring 2006.
Pragmatics.
1 Introduction to Computational Linguistics Eleni Miltsakaki AUTH Spring 2006-Lecture 4.
1 Introduction to Computational Linguistics Eleni Miltsakaki AUTH Fall 2005-Lecture 2.
Meaning and Language Part 1.
TRANSFORMATIONAL GRAMMAR An introduction. LINGUISTICS Linguistics Traditional Before 1930 Structural 40s -50s Transformational ((Chomsky 1957.
Functional Dependency Grammars
Generative Grammar(Part ii)
March 1, 2009 Dr. Muhammed Al-Mulhem 1 ICS 482 Natural Language Processing INTRODUCTION Muhammed Al-Mulhem March 1, 2009.
Lecture 1, 7/21/2005Natural Language Processing1 CS60057 Speech &Natural Language Processing Autumn 2005 Lecture 1 21 July 2005.
9/8/20151 Natural Language Processing Lecture Notes 1.
Lecture 12: 22/6/1435 Natural language processing Lecturer/ Kawther Abas 363CS – Artificial Intelligence.
Computational Linguistics INTroduction
1 Computational Linguistics Ling 200 Spring 2006.
Help me!... I’m being polluted… Too dirty!!! I’m being destroyed… Mommy! We are going to be killed! Savage!!!... What are these pictures talking about?
Natural Language Processing Rogelio Dávila Pérez Profesor – Investigador
Chapter 6. Semantics is the study of the meaning of words, phrases and sentences. In semantic analysis, there is always an attempt to focus on what the.
Prof Cecilia Montorsi UNIT 1 SOME BASIC CONCEPTS BASED ON LOCK, Graham. Functional English Grammar. USA. CUP Pp 1-11.
Postgraduate Diploma in Translation Lecture 1 Computers and Language.
Introduction to Linguistics Ms. Suha Jawabreh Lecture 18.
Introduction to CL & NLP CMSC April 1, 2003.
1 Introduction to Linguistics Teacher: Simon Smith ( 史尚明 ) – “Dr Smith”, “Simon” or “ 老師 ”: OK – “Smith” or “Teacher”: not OK This semester’s course: –
1 Special Electives of Comp.Linguistics: Processing Anaphoric Expressions Eleni Miltsakaki AUTH Fall 2005-Lecture 2.
Natural Language Processing Daniele Quercia Fall, 2000.
THE NATURE OF TEXTS English Language Yo. Lets Refresh So we tend to get caught up in the themes on English Language that we need to remember our basic.
1 Relationship between Cognitive Psychology and Other Disciplines Eysenck, Michael W. and Mark T. Kean Cognitive Psychology: A Student's Handbook,
A very, very brief introduction to linguistics Computational Linguistics, NLL Riga 2008, by Pawel Sirotkin 1.
NLP ? Natural Language is one of fundamental aspects of human behaviors. One of the final aim of human-computer communication. Provide easy interaction.
WHAT IS LINGUISTICS? MGTER RAMON GUERRA. Each human language is a complex of knowledge and abilities enabling speakers of the language to communicate.
1 Introduction to Computational Linguistics Eleni Miltsakaki AUTH Fall 2005-Lecture 4.
October 2005CSA3180 NLP1 CSA3180 Natural Language Processing Introduction and Course Overview.
CSA2050 Introduction to Computational Linguistics Lecture 1 Overview.
CSA2050 Introduction to Computational Linguistics Lecture 1 What is Computational Linguistics?
An Evaluation Tool for Natural Language Processing Systems Audrey N. Mbeje Department of Computer Science Ball State University November 09, 2000.
Introduction to Linguistics
1 Introduction to Computational Linguistics Eleni Miltsakaki AUTH Spring 2006-Lecture 8.
Introduction to Computational Linguistics (LIN3060) Lecture 1 Computers and Language.
Introduction to Linguistics Class # 1. What is Linguistics? Linguistics is NOT: Linguistics is NOT:  learning to speak many languages  evaluating different.
CSE467/567 Computational Linguistics Carl Alphonce Computer Science & Engineering University at Buffalo.
1 Special Electives of Comp.Linguistics: Processing Anaphoric Expressions Eleni Miltsakaki AUTH Fall 2005-Lecture 1.
Writing the audio story Journalism/New Media II MCOM 258 Summer 2009.
CS460/IT632 Natural Language Processing/Language Technology for the Web Lecture 1 (03/01/06) Prof. Pushpak Bhattacharyya IIT Bombay Introduction to Natural.
Pragmatics Nuha Alwadaani.
1 Introduction to Computational Linguistics Eleni Miltsakaki AUTH Spring 2006-Lecture 2.
Unit 10 It’s a nice day, isn’t it? Section A. Complete the following tag questions. 1.He is a student, ? 2. You can speak English, ? 3. We play football.
Yule: “Words themselves do not refer to anything, people refer” Reference and inference Pragmatics: Reference and inference.
Natural Language Processing (NLP)
Pragmatics. Definitions of pragmatics Pragmatics is a branch of general linguistics like other branches that include: Phonetics, Phonology, Morphology,
Linguistics at SOAS Insight Day – 2 nd March 2016.
Unit 1 Try not to translate every word. Module 1 How to learn English.
MENTAL GRAMMAR Language and mind. First half of 20 th cent. – What the main goal of linguistics should be? Behaviorism – Bloomfield: goal of linguistics.
King Faisal University جامعة الملك فيصل Deanship of E-Learning and Distance Education عمادة التعلم الإلكتروني والتعليم عن بعد [ ] 1 جامعة الملك فيصل عمادة.
INFINITIVES By Mr. LO Chung-kwong All rights reserved.2002.
Unit 4 Don’t eat in class! SectionA(1a-1c) rule n. 规则;规章 arrive v. 到达 (be) on time 准时 hallway n. 走廊 ; 过道 hall n. 大厅;礼堂 dining hall 餐厅 listen v. 听;倾听.
English Syntax Week 1. Introduction.
Pragmatics: Reference and inference
Introduction to Computational Linguistics
Presentation transcript:

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

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 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 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 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 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 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 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 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

10

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 Language technology ALICE the chatbox – Jabberwacky – USC demo for learning Arabic – movhttp:// mov