Way Topics

7/29/2019 Way Topics

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Research TopicsNatural Language Processing

Image Processing

CSC 3990


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Natural Language Processing

CSC 3990


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What is NLP?

Natural Language Processing (NLP)

Computers use (analyze, understand,

generate) natural language

A somewhat applied field

Computational Linguistics (CL)

Computational aspects of the human

language faculty

More theoretical


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Why Study NLP?

Human language interesting & challenging

NLP offers insights into language

Language is the medium of the web Interdisciplinary: Ling, CS, psych, math

Help in communication

With computers (ASR, TTS) With other humans (MT)

Ambitious yet practical


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Goals of NLP

Scientific Goal Identify the computational machinery

needed for an agent to exhibit various

forms of linguistic behavior

Engineering Goal

Design, implement, and test systems

that process natural languages for

practical applications


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Applications

speech processing: get flight information or booka hotel over the phone

information extraction: discover names of people

and events they participate in, from a document machine translation: translate a document from

one human language into another

question answering: find answers to natural

language questions in a text collection ordatabase

summarization: generate a short biography ofNoam Chomsky from one or more news articles


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General Themes

Ambiguity of Language

Language as a formal system

Computation with human language Rule-based vs. Statistical Methods

The need for efficiency


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Topic Ideas

1.Text to Speech artificial voices

2.Speech Recognition - understanding

3.Textual Analysis readability4.Plagiarism Detection candidate selection

5.Intelligent Agents machine interaction


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Text to Speech artificial voice

Text Input

Break text into phonemes Match phonemes to voice elements

Concatenate voice elements Manipulate pitch and spacing

Output results

Research question: How can a human voice be

used to produce an artificial voice? Model Talker - opportunities for active, hands-on

research (http://www.modeltalker.com)
http://www.modeltalker.com/http://www.modeltalker.com/


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Speech Recognition

Spoken Input

Identify words and phonemes in speech Generate text for recognized word parts

Concatenate text elements Perform spelling, grammar and context checking

Output results

Research question: How can speech recognition

assist a deaf student taking notes in class? VUST Villanova University Speech Transcriber

(http://www.csc.villanova.edu/~tway/publications/wayAT08.pdf)
http://www.csc.villanova.edu/~tway/publications/wayAT08.pdfhttp://www.csc.villanova.edu/~tway/publications/wayAT08.pdf


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Textual Analysis - Readability

Text Input

Analyze text & estimate readability

Grade level of writing

Consistency of writing

Appropriateness for certain educ. level

Output results

Research question: How can computeranalyze text and measure readability?

Opportunities for hands-on research


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Plagiarism Detection

Text Input

Analyze text & locate candidates

Find one or more passages that might be plagiarized

Algorithm tries to do what a teacher does

Search on Internet for candidate matches

Output results

Research question: What algorithms work likehumans when finding plagiarism?

Experimental CS research


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Intelligent Agents

Example: ELIZA

AIML: Artificial Intelligence Modeling Lang.

Human types something

Computer parses, understands, and generates

response

Response is viewed by human

Research question: How can computersunderstand and generate human writing?

Also good area for experimentation


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Image Processing

CSC 3990

Some slides from Xin Li lecture notes, West Virginia Univ.


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What is Image Processing?

Digital Image Processing

Analog transmission in 1920

Early improvements in 1920s

Required digitalcomputer (1948)

Rapid advancement since


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Historical Background

Newspaper industry used

Bartlane cable picture

transmission system to sendpictures by submarine cable

between London and New

York in 1920s

The number of distinct gray

levels coded by Bartlanesystem was improved from 5

to 15 by the end of 1920s


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Digital Image Processing

The images in previous slides are digital(now), but they are NOT the result of DIP

Digital Image Processingis

Processing digital images by a digitalcomputer

DIP requires a digital computer and other

supporting technologies (e.g., data storage,display and transmission)


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Cool Applications

The first picture of moon

by US spacecraftRanger 7

on July 31, 1964 at9:09AM EDT

Digitization

Compression

Error Recovery

Sir Godfrey N. Housefield and Prof.

Allan M. Cormack shared 1979

Nobel Prize in Medicine for theinvention of CT

Enhancement

Edges, Contrast,

Brightness, etc.


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Acquisition

Digital cameras, scanners

MRI and Ultrasound imaging

Infrared and microwave imaging

Transmission

Internet, wireless communication

Display

Printers, LCD monitor, digital TV

Past 20 Years


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Photography


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Motion Pictures


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Law Enhancement and Biometrics
http://www.gait.ecs.soton.ac.uk/treadmill','treadmill_anim.gif


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Remote Sensing

Hurricane Andrew

taken by NOAA GEOS

America at night

(Nov. 27, 2000)


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Thermal Images

Human body disperses

heat (red pixels)

Different colors indicate

varying temperatures

Operate in infrared frequency


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Medical Diagnostics

chest head

Operate in X-ray frequency


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PET and Astronomy

Positron Emission Tomography

Cygnus Loop in the

constellation of Cygnus

Operate in gamma-ray frequency


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Cartoon Pictures (Non-photorealistic)


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Synthetic Images in Gaming

Age of Empire IIIby Ensemble Studios


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Virtual Reality (Photorealistic)


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General Themes

Human vision is limited

Digital images contain more information

that humans perceive

Computers can use algorithms to extract

more information from digital images

Computers can acquire, manipulate,

compress, transmit and modify images


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Topic Ideas

1.Biometrics identifying faces & retinas

2.Target Acquisition see a tank from space

3.Computer Vision detect microscopic flaws in

manufacturing4.Assistive Technology convert visual images

into tactile or textual form

5.Entertainment remove red eye, morph faces,

digital filmmaking, movie magic6. Image Description use 3D dictionary to

describe contents of 2D image

Documents

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