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CS4705 Natural Language Processing Fall 2007

Explore how machines recognize, generate text and speech, search large corpora, translate languages, and more. Dive into NLP concepts like morphology, syntax, semantics, and pragmatics. Learn computational techniques for language processing and applications in language generation, summarization, translation, and dialogue systems. Get ready for a deep dive into the world of natural language processing with a focus on text and speech.

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CS4705 Natural Language Processing Fall 2007

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  1. CS4705 Natural Language Processing Fall 2007 CS 4705

  2. What will we study in this course? • How can machines recognize and generate text and speech? • Current real world applications? • Searching very large text and speech corpora: e.g. the Web • Translating between one language and another: e.g. Arabic and English • Summarizing very large amounts of text: e.g. your email, the news • Building dialogue systems: e.g. Amtrak’s ‘Julie’

  3. Open Problems in NLP • If you want to find all references to union activities in New York, what keywords do you specify? • Union…and…Unions? United? Uniform? Onion? • Activities…and…Activity? Active? Actor? Action? • Morphology: how words are composed of smaller units of meaning – which words are related? • What’s the same about these sentences? Different? • John hit Bill • Bill was hit by John

  4. Bill, John hit • Who John hit was Bill • Syntax: the way words are grouped together into larger constituents and phrases and the way these phrases can be ordered – how sentences are related • Semantics: the context-independent ‘meaning’ of utterances (the similar part) • Pragmatics: the context-dependent ‘meaning’ of utterances (some of the different part) • If you want to find travel information about Nice, France why might you get documents on Nice views in Cleveland? • Word Sense Disambiguation: how to distinguish the different meanings of words spelled the same

  5. Course Focus: NLP for Text and Speech • Morphology, syntax, semantics, pragmatics/discourse • Human language phenomena • Techniques and algorithms for computational language processing • Parsing, information extraction/retrieval, statistical and machine learning approaches (corpus linguistics) • Applications: Language generation and summarization, machine translation, dialogue systems and spoken language processing • Next term: CS 4706 focuses on spoken NLP

  6. Instructor • Julia Hirschberg • Computational Linguist in CS • Focus: Spoken Language Processing • Lab: The Speech Lab, CEPSR 7LW3-A • Research: • Deceptive speech • Charismatic speech: • Emotional speech: anger, uncertainty • Speech summarization: Broadcast News • Spoken Dialogue Systems: Games Corpus • `Translating Prosody’: English – Mandarin • Course Details

  7. Is She Lying?

  8. Bureaucracy • Instructor: Julia Hirschberg • (julia@cs.columbia.edu) • Office and hours: CEPSR 705, TBA • Teaching Assistant: Frank Enos • (frank@cs.columbia.edu) • Office and hours: CEPSR 726 TBA • Syllabus available at http://www1.cs.columbia.edu/~julia/cs4705/syllabus07.html

  9. Text: Daniel Jurafsky and James H. Martin, Speech and Language Processing, Prentice-Hall, 2000 (available at CU Bookstore) • Note errata available on website; check before reading each chapter please • Check courseworks • Assignments: • 3 homework assignments • Midterm and final exams • Four ‘free’ late days for homework assignments • You must get a CS account • Evaluation: 50% homework + 50% exams

  10. Academic Integrity Copying or paraphrasing someone's work (code included), or permitting your own work to be copied or paraphrased, even if only in part, is forbidden, and will result in an automatic grade of 0 for the entire assignment or exam in which the copying or paraphrasing was done. Your grade should reflect your own work. If you are going to have trouble completing an assignment, talk to the instructor or TA in advance of the due date please. Everyone: Read/write protect your homework files at all times.

  11. For Next Class • Look at syllabus • Read Chapters 1-2 of J&M • Questions?

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