1. Research Topics Natural Language Processing Image Processing
CSC 3990

2. Natural Language Processing
CSC 3990

3. 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

4. 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

5. Goals of NLP Scientific Goal Engineering 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

6. Applications
speech processing: get flight information or book a 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 or database
summarization: generate a short biography of Noam Chomsky from one or more news articles

7. General Themes Ambiguity of Language Language as a formal system
Computation with human language
Rule-based vs. Statistical Methods
The need for efficiency

8. Topic Ideas Text to Speech – artificial voices
Speech Recognition - understanding
Textual Analysis – readability
Plagiarism Detection – candidate selection
Intelligent Agents – machine interaction

9. 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 (

10. 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 (

11. 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 computer analyze text and measure readability?
Opportunities for hands-on research

12. 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 like humans when finding plagiarism?
Experimental CS research

13. 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 computers “understand” and “generate” human writing?
Also good area for experimentation

14. CSC 3990 Some slides from Xin Li lecture notes, West Virginia Univ.
Image Processing
CSC 3990
Some slides from Xin Li lecture notes, West Virginia Univ.

15. What is Image Processing?
Digital Image Processing
Analog transmission in 1920
Early improvements in 1920s
Required digital computer (1948)
Rapid advancement since

16. Historical Background
Newspaper industry used Bartlane cable picture transmission system to send pictures by submarine cable between London and New York in 1920s
The number of distinct gray levels coded by Bartlane system was improved from 5 to 15 by the end of 1920s

17. Digital Image Processing
The images in previous slides are digital (now), but they are NOT the result of DIP
Digital Image Processing is
Processing digital images by a digital computer
DIP requires a digital computer and other supporting technologies (e.g., data storage, display and transmission)

18. Cool Applications The first picture of moon by US spacecraft Ranger 7
on July 31, 1964 at 9:09AM EDT
Sir Godfrey N. Housefield and Prof. Allan M. Cormack shared 1979 Nobel Prize in Medicine for the invention of CT
Digitization
Compression
Error Recovery
Enhancement
Edges, Contrast, Brightness, etc.

19. Past 20 Years Acquisition Transmission Display
Digital cameras, scanners
MRI and Ultrasound imaging
Infrared and microwave imaging
Transmission
Internet, wireless communication
Display
Printers, LCD monitor, digital TV

20. Photography

21. Motion Pictures

22. Law Enhancement and Biometrics

23. Remote Sensing America at night Hurricane Andrew (Nov. 27, 2000)
taken by NOAA GEOS
America at night
(Nov. 27, 2000)

24. Different colors indicate
Thermal Images
Operate in infrared frequency
Human body disperses
heat (red pixels)
Different colors indicate
varying temperatures

25. Medical Diagnostics
Operate in X-ray frequency
chest
head

26. constellation of Cygnus
PET and Astronomy
Operate in gamma-ray frequency
Cygnus Loop in the
constellation of Cygnus
Positron Emission Tomography

27. Cartoon Pictures (Non-photorealistic)

28. Synthetic Images in Gaming
Age of Empire III by Ensemble Studios

29. Virtual Reality (Photorealistic)

30. 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

31. Topic Ideas Biometrics – identifying faces & retinas
Target Acquisition – see a tank from space
Computer Vision – detect microscopic flaws in manufacturing
Assistive Technology – convert visual images into tactile or textual form
Entertainment – remove red eye, morph faces, digital filmmaking, movie magic
Image Description – use 3D dictionary to describe contents of 2D image