CS4705 Natural Language Processing Fall 2009. What will we study in this course? How can machines recognize and generate text and speech? – Human language.

Slides:



Advertisements
Similar presentations
European Masters Program in Language and Communication Technologies Free University.
Advertisements

CS 4705 Natural Language Processing Julia Hirschberg COMS 4705 Fall 2010.
INTERNATIONAL CONFERENCE ON NATURAL LANGUAGE PROCESSING NLP-AI IIIT-Hyderabad CIIL, Mysore ICON DECEMBER, 2003.
For Friday No reading Homework –Chapter 23, exercises 1, 13, 14, 19 –Not as bad as it sounds –Do them IN ORDER – do not read ahead here.
NLP and Speech Course Review. Morphological Analyzer Lexicon Part-of-Speech (POS) Tagging Grammar Rules Parser thethe – determiner Det NP → Det.
CSE111: Great Ideas in Computer Science Dr. Carl Alphonce 219 Bell Hall Office hours: M-F 11:00-11:
Introduction to Computational Linguistics Lecture 2.
1 Natural Language Processing for the Web Prof. Kathleen McKeown 722 CEPSR, Office Hours: Wed, 1-2; Tues 4-5 TA: Yves Petinot 719 CEPSR,
CS 4705 Lecture 1 CS4705 Introduction to Natural Language Processing.
Center for Computational Learning Systems Independent research center within the Engineering School NLP people at CCLS: Mona Diab, Nizar Habash, Martin.
1/7 INFO60021 Natural Language Processing Harold Somers Professor of Language Engineering.
Columbia’s Vision for Tomorrow’s Global Intelligent Systems Henning Schulzrinne, Chair Department of Computer Science October 13, 2005 Bill Gates/CS Faculty.
1 Natural Language Processing for the Web Prof. Kathleen McKeown 722 CEPSR, Office Hours: Wed, 1-2; Mon 3-4 TA: Fadi Biadsy 702 CEPSR,
CS 4705 Natural Language Processing What is Natural Language Processing? The study of human languages and how they can be represented computationally.
Center for Computational Learning Systems Independent research center within the Engineering School NLP people at CCLS: Mona Diab, Nizar Habash, Martin.
CS4705 Natural Language Processing Fall What will we study in this course? How can machines recognize and generate text and speech? – Human language.
1/16 LELA Language and Computers Harold Somers Professor of Language Engineering.
تمرين شماره 1 درس NLP سيلابس درس NLP در دانشگاه هاي ديگر ___________________________ راحله مکي استاد درس: دکتر عبدالله زاده پاييز 85.
Introduction to Artificial Intelligence Prof. Kathleen McKeown 722 CEPSR, TAs: Kapil Thadani 724 CEPSR, Phong Pham TA Room.
CS4705 Natural Language Processing Fall  How can machines recognize and generate text and speech? ◦ Human language phenomena ◦ Theories, often.
Natural Language Processing Prof: Jason Eisner Webpage: syllabus, announcements, slides, homeworks.
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.
1 Ling 569: Introduction to Computational Linguistics Jason Eisner Johns Hopkins University Tu/Th 1:30-3:20 (also this Fri 1-5)
Lecture 12: 22/6/1435 Natural language processing Lecturer/ Kawther Abas 363CS – Artificial Intelligence.
Computational Linguistics Yoad Winter *General overview *Examples: Transducers; Stanford Parser; Google Translate; Word-Sense Disambiguation * Finite State.
1 Natural Language Processing Gholamreza Ghassem-Sani Fall 1383.
Intro to Natural Language Processing1 Introduction to Natural Language Processing August 28, 2012 Lecture #1.
+ 1. Pragmatics. - What is pragmatics? - Context 2. Speech acts. - direct speech acts - indirect speech acts.
1 Computational Linguistics Ling 200 Spring 2006.
CS 4705 Natural Language Processing Fall 2010 What is Natural Language Processing? Designing software to recognize, analyze and generate text and speech.
CS 390 Introduction to Theoretical Computer Science.
Language Development: The Course Jan. 6, The Course Designed to give students a comprehensive understanding of language development, primarily in.
Natural Language Processing Guangyan Song. What is NLP  Natural Language processing (NLP) is a field of computer science and linguistics concerned with.
THE BIG PICTURE Basic Assumptions Linguistics is the empirical science that studies language (or linguistic behavior) Linguistics proposes theories (models)
CS 4705 Natural Language Processing Fall 2010 What is Natural Language Processing? Designing software to recognize, analyze and generate text and speech.
LTI Education Committee Report Alon Lavie LTI Retreat March 2, 2012.
Research Topics CSC Parallel Computing & Compilers CSC 3990.
1 CS 2710, ISSP 2610 Foundations of Artificial Intelligence introduction.
1 CSI 5180: Topics in AI: Natural Language Processing, A Statistical Approach Instructor: Nathalie Japkowicz Objectives of.
October 2005CSA3180 NLP1 CSA3180 Natural Language Processing Introduction and Course Overview.
CSA2050 Introduction to Computational Linguistics Lecture 1 Overview.
The Difference Between Linguistics and “Lingvistika”
Summary and Questions for Psycholinguistics. Psycholinguistics as cognitive study Stimuli (makeup of information) processing (functions & operations)
For Wednesday No reading Homework –Chapter 23, exercise 15 –Process: 1.Create 5 sentences 2.Select a language 3.Translate each sentence into that language.
ICS 482: Natural language Processing Pre-introduction
For Monday Read chapter 24, sections 1-3 Homework: –Chapter 23, exercise 8.
For Friday Finish chapter 24 No written homework.
For Monday Read chapter 26 Last Homework –Chapter 23, exercise 7.
CSE467/567 Computational Linguistics Carl Alphonce Computer Science & Engineering University at Buffalo.
Natural Language Processing Chapter 1 : Introduction.
CS460/IT632 Natural Language Processing/Language Technology for the Web Lecture 1 (03/01/06) Prof. Pushpak Bhattacharyya IIT Bombay Introduction to Natural.
1 An Introduction to Computational Linguistics Mohammad Bahrani.
CS 4705 Natural Language Processing Who am I? Julia Hirschberg –Computational Linguist in CS –Focus: Spoken Language Processing –Lab: The Speech Lab,
1 CPA: Where do we go from here? Research Institute for Information and Language Processing, University of Wolverhampton; UPF Barcelona; University of.
For Monday Read chapter 26 Homework: –Chapter 23, exercises 8 and 9.
Programming In Perl CSCI-2230 Wednesday, 4pm-5:50pm Paul Lalli - Instructor.
Inter-disciplines and applied linguistics. Inter-disciplines: Sociolinguistics looks at how language is used in a social context, e.g. –language use and.
Natural Language Processing Tasneem Ghnaimat Spring 2013.
Lecture 1: Introduction Why Astronomy is Fun The Scientific Method Group Activities in Lecture Reading: E5, Appendix 1, 2 (5 pages) Homework: WebCT Diagnostic.
Related Courses CMPT 411: Knowledge Representation. Mainly Logic. CMPT 413: Computational Linguistics. Dealing with Natural Language. CMPT 419/726: Often.
Introduction to Artificial Intelligence Prof. Kathleen McKeown 722 CEPSR Tas: Andrew Rosenberg Speech Lab, 7 th Floor CEPSR Sowmya Vishwanath TA Room.
Introduction to Machine Translation
Introduction to Computing
Introduction to Machine Translation
CS224N Section 3: Corpora, etc.
Artificial Intelligence 2004 Speech & Natural Language Processing
Presentation transcript:

CS4705 Natural Language Processing Fall 2009

What will we study in this course? How can machines recognize and generate text and speech? – Human language phenomena – Theories, often drawn from linguistics, psychology – Algorithms – Applications

Syntax Word Order – John hit Bill – Bill was hit by John – Bill hit John – Bill, John hit – Who John hit was Bill

Semantics Word meaning – John picked up a bad cold. – John picked up a large rock. – John picked up Radio Netherlands on his radio.

Pragmatics – The influence of context “Going Home'' - A play in one act Scene 1: Pennsylvania Station, NY Bonnie: Long Beach? Passerby: Downstairs, LIRR Station.

Scene 2: Ticket Counter, LIRR Station Bonnie: Long Beach? Clerk: $4.50.

Current Real World Applications Searching very large text and speech corpora: e.g. the Web Question answering over the web Translating between one language and another: e.g. Arabic and English Summarizing very large amounts of text: e.g. your , the news Dialogue systems: e.g. Amtrak’s ‘Julie’Julie

Instructor Kathy McKeown Office: 722 CEPSR Head NLP GroupNLP Group 25 years at Columbia, Department Chair for 6 Research – Summarization – Question Answering – Language Generation – Multimedia Explanation

Logistics Instructor: Kathy McKeown – – Office and hours: CEPSR 722, Tues 4-5, Wed 4-5 Syllabus available at