CSE573 Autumn 1997 1 02/20/98 Planning/Language Administrative –PS3 due 2/23 –Midterms back today –Next topic: Natural Language Processing reading Chapter.

Slides:



Advertisements
Similar presentations
Natural Language Processing (or NLP) Reading: Chapter 1 from Jurafsky and Martin, Speech and Language Processing: An Introduction to Natural Language Processing,
Advertisements

Artificial Intelligence Created by Korbut Fyodor FTF,
Please check. Announcements 1.Don't forget your plagiarism certificate next week. You must turn that in in order to stay enrolled in the class. 2.The.
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.
Natural Language and Speech Processing Creation of computational models of the understanding and the generation of natural language. Different fields coming.
CSE111: Great Ideas in Computer Science Dr. Carl Alphonce 219 Bell Hall Office hours: M-F 11:00-11:
Language is very difficult to put into words. -- Voltaire What do we mean by “language”? A system used to convey meaning made up of arbitrary elements.
By Rohana Mahmud (NLP week 1-2)
Multiagent Systems and Societies of Agents
1 Phonetics Study of the sounds of Speech Articulatory Acoustic Experimental.
PSY 369: Psycholinguistics Some basic linguistic theory part3.
تمرين شماره 1 درس NLP سيلابس درس NLP در دانشگاه هاي ديگر ___________________________ راحله مکي استاد درس: دکتر عبدالله زاده پاييز 85.
Chapter 12: Intelligent Systems in Business
A Conversational Agent to Navigate in Virtual Worlds CHI 2000 Workshop on Natural Language Interfaces The Hague, The Netherlands Pierre Nugues, Christophe.
9-Aug-15 Vocabulary. Programming Vocabulary Watch closely, you might even want to take some notes. There’s a short quiz at the end of this presentation!
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.
CAREERS IN LINGUISTICS OUTSIDE OF ACADEMIA CAREERS IN INDUSTRY.
9/8/20151 Natural Language Processing Lecture Notes 1.
Some Thoughts to Consider 13 What do we really mean by ‘learning’ in a software system? Can humans or systems learn anything that they don’t already know?
Chapter 10 Natural Language Processing Xiu-jun GONG (Ph. D) School of Computer Science and Technology, Tianjin University
Lecture 12: 22/6/1435 Natural language processing Lecturer/ Kawther Abas 363CS – Artificial Intelligence.
April 2008Historical Perspectives on NLP1 Historical Perspectives on Natural Language Processing Mike Rosner Dept Artificial Intelligence
1 Natural Language Processing Gholamreza Ghassem-Sani Fall 1383.
1 Computational Linguistics Ling 200 Spring 2006.
A Procedural Model of Language Understanding Terry Winograd in Schank and Colby, eds., Computer Models of Thought and Language, Freeman, 1973 발표자 : 소길자.
Introduction to CL & NLP CMSC April 1, 2003.
ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.
Artificial Intelligence By Michelle Witcofsky And Evan Flanagan.
Language. Phonetics is the study of how elements of language are physically produced.
How Solvable Is Intelligence? A brief introduction to AI Dr. Richard Fox Department of Computer Science Northern Kentucky University.
Dept. of Computer Science University of Rochester Rochester, NY By: James F. Allen, Donna K. Byron, Myroslava Dzikovska George Ferguson, Lucian Galescu,
1 CSI 5180: Topics in AI: Natural Language Processing, A Statistical Approach Instructor: Nathalie Japkowicz Objectives of.
NLP ? Natural Language is one of fundamental aspects of human behaviors. One of the final aim of human-computer communication. Provide easy interaction.
October 2005CSA3180 NLP1 CSA3180 Natural Language Processing Introduction and Course Overview.
Course Instructor: K ashif I hsan 1. Chapter # 1 Kashif Ihsan, Lecturer CS, MIHE2.
ICS 482: Natural language Processing Pre-introduction
CSE573 Autumn /27/98 Natural Language Processing Administrative –New version of PS4 on the Web different interface to the Truckworld more extra.
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.
CSE573 Autumn /23/98 Natural Language Processing Administrative –PS3 due today –PS4 out Wednesday, due Friday 3/13 (last day of class) special.
CSE467/567 Computational Linguistics Carl Alphonce Computer Science & Engineering University at Buffalo.
FOUNDATION IN INFORMATION TECHNOLOGY (CS-T-101) TOPIC : INFORMATION SYSTEM – SOFTWARE.
Natural Language Processing Chapter 1 : Introduction.
Introduction to Artificial Intelligence CS 438 Spring 2008 Today –AIMA, Chapter 1 –Defining AI Next Tuesday –Intelligent Agents –AIMA, Chapter 2 –HW: Problem.
CS460/IT632 Natural Language Processing/Language Technology for the Web Lecture 1 (03/01/06) Prof. Pushpak Bhattacharyya IIT Bombay Introduction to Natural.
For Friday Finish chapter 23 Homework –Chapter 23, exercise 15.
Higher Vision, language and movement. Strong AI Is the belief that AI will eventually lead to the development of an autonomous intelligent machine. Some.
LANGUAGE IMPAIRED. ELIGIBILITY CRITERIA Language Impaired (LI) An impairment in the language system is an abnormal processing or production of: Form including.
Pragmatics and Text Analysis Chapter 6.  concerned with the how meaning is communicated by the speaker (writer) and interpreted by the listener (reader)
Language Language - a system for combining symbols (such as words) so that an unlimited number of meaningful statements can be made for the purpose of.
1 An Introduction to Computational Linguistics Mohammad Bahrani.
CSE573 Autumn /02/98 Natural Language Processing Administrative –PS4 support code now in the NT course area Truckworld interface (stop, start,
For Monday Read chapter 26 Homework: –Chapter 23, exercises 8 and 9.
NATURAL LANGUAGE PROCESSING
Intelligent Control Methods Lecture 2: Artificial Intelligence Slovak University of Technology Faculty of Material Science and Technology in Trnava.
Basics of Natural Language Processing Introduction to Computational Linguistics.
Chapter 11 Language. Some Questions to Consider How do we understand individual words, and how are words combined to create sentences? How can we understand.
The Hebrew University of Jerusalem School of Engineering and Computer Science Academic Year: 2011/2012 Instructor: Jeff Rosenschein.
Teaching Machine to Listen Sol Lerner Chapter 25.
CSE573 Autumn /13/98 Finished Administrative –Final exam Tuesday, Mar. 17, 2:30-4:20 p.m., here –Additional help today after class Saturday
Artificial intelligence (AI)
Unit 3 Language Disabilities
Course Instructor: knza ch
Natural Language Processing
Artificial Intelligence 2004 Speech & Natural Language Processing
Information Retrieval
Presentation transcript:

CSE573 Autumn /20/98 Planning/Language Administrative –PS3 due 2/23 –Midterms back today –Next topic: Natural Language Processing reading Chapter 10; skip 10.8 and 10.9 Last time –extensions to the operator language conditional effects universal quantification –reading a UCPOP plan output This time –Graphplan –Natural language processing

CSE573 Autumn NLP Perspective An interesting cognitive problem –language is the most “human” communication modality, so it seems impossible to understand human intelligence without understanding how language works –Turing test looked on ability to communicate in an unrestricted natural language dialogue as the definition of intelligence An interesting practical problem: incredible extensions to usefulness of computers if problems could be solved in –speech recognition and understanding (no more phone menus!) –handwriting recognition and understanding (a PDA that actually works) –machine translation (electronic funds transfers and more complex multi- national transactions) –text recognition (intelligent information retrieval)

CSE573 Autumn The main problem Understanding language is “AI Complete” –in order to do it you have to understand every other facet of intelligence as well --- planning, reasoning about physical systems, geometrical and spatial reasoning, diagnosis, etc. etc. The history of natural language processing in AI is a process of discovering just how difficult and deep the problem is Ways to make the problem easier –work in limited domains (newspaper stories about earthquakes) –work with simpler syntax (will respond to information requests or to simple commands but cannot understand arbitrary sentences about the domain). Example: electronic funds transfers; intelligent database front-ends; Truckworld scenarios

CSE573 Autumn The usual breakdown of language processing tasks Signal understanding: translate signals (spoken speech or written characters) into some internal symbolic form. Produce phonemes or characters. Phonology: group phonemes into morphemes Morphology: group morphemes into words Syntax: parse words into phrases, phrases into sentences Semantics: connect words to objects and concepts in some internal representation language Pragmatics: infer what is desired from what is said in a sentence Discourse: constructing an argument, negotiating an agreement, (communication among agents) We are here Bottom up processing Top down processing

CSE573 Autumn Our Main Task: A Command Processor The system will parse, interpret and execute commands in a simple world –Blocksworld: “Pick up the green sphere on top of the yellow cube” “Put it down next to the red cube.” –Truckworld: “Recycle the red broken glass.” “Refuel using the fuel drum at position 7.” Parsing: is the sentence well formed? Semantic Interpretation: –does the command make sense given the current state of the world? –what do the pronouns refer to? Execution: simple call to an execution system (Macrops or behaviors)

CSE573 Autumn Our Limited Problem Arm can lift at most one object at a time Pyramid can be put on top of a block but not below Sphere cannot be put on top or below any block Actions pick up top block at current position put down block being held move to another position