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Amity School of Engineering & Technology
Natural Language Processing
Amity School of Engineering & Technology
What is Natural Language Processing?
• NLP is an interdisciplinary field that uses computational
methods to:
o Investigate the properties of written human language and
model the cognitive mechanisms underlying the
understanding and production of written language.
o Develop novel practical applications involving the
intelligent processing of written human language by
computer.
Amity School of Engineering & Technology
What is NLP? (cont.)
• NLP plays a big part in Machine learning techniques:
o automating the construction and adaptation of machine
dictionaries
o modeling human agents' desires and beliefs
 essential component of NLP
 closer to AI
• We will focus on two main types of NLP:
o Human-Computer Dialogue Systems
o Machine Translation
Amity School of Engineering & Technology
4
Language Processing
• Level 1 – Speech sound (Phonetics & Phonology)
• Level 2 – Words & their forms (Morphology,
Lexicon)
• Level 3 – Structure of sentences (Syntax, Parsing)
• Level 4 – Meaning of sentences (Semantics)
• Level 5 – Meaning in context & for a purpose
(Pragmatics)
• Level 6 – Connected sentence processing in a larger
body of text (Discourse)
Amity School of Engineering & Technology
5
Examples of Levels
• L1 : sound
• L2 : Dog - Dog(s), Dog(ged)
Lady – Lad(ies)
Should we store all forms of words in the lexicon?
• L3 : Ram goes to market (right)
goes Ram to the market (wrong)
• L4 : translation from unstructured to structured
representation
go : (event)
agent : Ram
source : ?
destination : market
Amity School of Engineering & Technology
6
Example (Contd.)
• L5 : User situation & context
“Is that water?” – the action to be performed is
different in a chemistry lab and on a dining table.
• L6 : Backward & forward references –
• Coreference resolution
“The man went near the dog. It bit him.”
Often co reference & ambiguity go together as in –
“The dog went near the cat. It bit it.”
Amity School of Engineering & Technology
Human-Computer Dialogue Systems
• Usually with the computer modelling a human dialogue
participan Will be able:
o To converse in similar linguistic style
o Discuss the topic
o Hopefully teach
Amity School of Engineering & Technology
Current Capabilities of Dialogue Systems
• Simple voice communication with machines
o Personal computers
o Interactive answering machines
o Voice dialing of mobile telephones
o Vehicle systems
o Can access online as well as stored information
• Currently working to improve
Amity School of Engineering & Technology
The Future of H-C Dialogue Systems
• The final end result of human computer dialogue systems:
o Seamless spoken interaction between a computer and a human
• This would be a major component of making an AI that can pass
the Turing Test
• Be able to have a computer function as a teacher
Amity School of Engineering & Technology
Human Computer Dialogue in Fiction
• Halo's Cortana AI
o Made from models of a real human brain
o Made to run the ship
o Made very human conversations
• Ender's Game series: Jane
o Made from "philotic connection"
o Human conversation
Amity School of Engineering & Technology
Problems of Human-Computer Dialogue
• At the moment, most common computer dialogue systems (call
systems, chatter bots, etc.) cannot handle arbitrary input
o In many cases, the computer can only respond to "expected"
speech
o Call systems often compensate with "Sorry, I didn't get that,"
when something unexpected is said.
Amity School of Engineering & Technology
Problems of Human-Computer Dialogue
• Computers need to be able to learn and process colloquial speech
• Needed to understand informal speakers:
o Understanding varied responses for call systems
o Accounting for variations in spoken numbers
• Processing colloquialisms is also necessary for seamless dialogue,
where the computer must avoid sounding too formal
o John Connor: "No, no, no, no. You gotta listen to the way people
talk. You don't say 'affirmative,' or [stuff] like that. You say 'no
problemo.' "
Amity School of Engineering & Technology
Successes of Human-Computer Dialogue
• So far, human-computer dialogue has been most successful in
applications where information about a specific topic is sought
from the computer.
o Electronic calling systems: company-specific
o Travel agents: specific to an airline or destination
• However, more complex systems of human-computer dialogue
have been produced which can interpret more varied input.
o Physics tutoring system (ITSPOKE) which can analyze and
explain errors in the response to a physics problem.
o Allows for more complex input than "Yes," "No," or "Flight
UA-93"
• These still cannot compare to true human-human dialogue.
Amity School of Engineering & Technology
Machine Translation
• Important for:
o accessing information in a foreign language
o communication with speakers of other languages
• The majority of documents on the world wide web are in
languages other than English
Amity School of Engineering & Technology
Statistical Translation
• Rule based
• Works relatively well with large sets of data
• Used probability to translate text
• Natural translations
• Google
Amity School of Engineering & Technology
Example Based Translation
• Converts "parallel" lines of text between language
• Only accurate for simple lines
• Minimal pairs are easy
• Analogy based
Amity School of Engineering & Technology
Paraphrasing
• Takes words and makes them simpler automatically
• For example in Spanish conjugated words like usado may be
changed to usar
Amity School of Engineering & Technology
Future of Machine Translation
• Goal:
o Aim to be able to flawlessly translate languages
• Link Human-Computer Dialogue and Machine Translation
• Have someone be able to talk in one language to a computer,
translate for another person
• Translated Video Chat
Amity School of Engineering & Technology
Machine Translation in Fiction
• Star Wars: C-3P0
o Interpreter
o Could hear and translate alien languages
o Final goal of machine translation
• Star Trek: Universal Translator
o Computer can seamlessly translate alien languages
Amity School of Engineering & Technology
Problems
• Works well only with predictable texts.
• Doesn't work well with domains where people want
translation the most:
o spontaneous conversations
o in person
o on the telephone
o and on the Internet.
Amity School of Engineering & Technology
Problems
• Computers can't deal with ambiguity, syntactic irregularity,
multiple word meanings and the influence of context.
Time flies like an arrow.
Fruit flies like a banana.
• Accurate translation requires an understanding of the text,
situation, and a lot of facts about the world in general.
The box is in the pen.
Amity School of Engineering & Technology
Problems
• The sign is describing a
restaurant (the Chinese
text, 餐厅, means
"dining hall").
• In the process of making
the sign, the producers
tried to translate Chinese
text into English with a
machine translation
system, but the
software didn't work,
producing the error
message,
"Translation Server Error."
• The software's user didn't
know English and thought
the error message was the
translation.
Amity School of Engineering & Technology
Successes
• Product knowledge bases need to be translated into multiple
languages
• Hiring a large multilingual support staff is expensive
• Machine translation is cheaper and accurate with predictable
texts.
• Microsoft, Autodesk, Symantec, and Intel use it.
o Makes customers happy
o Still readable though slightly chunkier than human
translations

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AI Intro to NLP_Module 3.ppt

  • 1. Amity School of Engineering & Technology Natural Language Processing
  • 2. Amity School of Engineering & Technology What is Natural Language Processing? • NLP is an interdisciplinary field that uses computational methods to: o Investigate the properties of written human language and model the cognitive mechanisms underlying the understanding and production of written language. o Develop novel practical applications involving the intelligent processing of written human language by computer.
  • 3. Amity School of Engineering & Technology What is NLP? (cont.) • NLP plays a big part in Machine learning techniques: o automating the construction and adaptation of machine dictionaries o modeling human agents' desires and beliefs  essential component of NLP  closer to AI • We will focus on two main types of NLP: o Human-Computer Dialogue Systems o Machine Translation
  • 4. Amity School of Engineering & Technology 4 Language Processing • Level 1 – Speech sound (Phonetics & Phonology) • Level 2 – Words & their forms (Morphology, Lexicon) • Level 3 – Structure of sentences (Syntax, Parsing) • Level 4 – Meaning of sentences (Semantics) • Level 5 – Meaning in context & for a purpose (Pragmatics) • Level 6 – Connected sentence processing in a larger body of text (Discourse)
  • 5. Amity School of Engineering & Technology 5 Examples of Levels • L1 : sound • L2 : Dog - Dog(s), Dog(ged) Lady – Lad(ies) Should we store all forms of words in the lexicon? • L3 : Ram goes to market (right) goes Ram to the market (wrong) • L4 : translation from unstructured to structured representation go : (event) agent : Ram source : ? destination : market
  • 6. Amity School of Engineering & Technology 6 Example (Contd.) • L5 : User situation & context “Is that water?” – the action to be performed is different in a chemistry lab and on a dining table. • L6 : Backward & forward references – • Coreference resolution “The man went near the dog. It bit him.” Often co reference & ambiguity go together as in – “The dog went near the cat. It bit it.”
  • 7. Amity School of Engineering & Technology Human-Computer Dialogue Systems • Usually with the computer modelling a human dialogue participan Will be able: o To converse in similar linguistic style o Discuss the topic o Hopefully teach
  • 8. Amity School of Engineering & Technology Current Capabilities of Dialogue Systems • Simple voice communication with machines o Personal computers o Interactive answering machines o Voice dialing of mobile telephones o Vehicle systems o Can access online as well as stored information • Currently working to improve
  • 9. Amity School of Engineering & Technology The Future of H-C Dialogue Systems • The final end result of human computer dialogue systems: o Seamless spoken interaction between a computer and a human • This would be a major component of making an AI that can pass the Turing Test • Be able to have a computer function as a teacher
  • 10. Amity School of Engineering & Technology Human Computer Dialogue in Fiction • Halo's Cortana AI o Made from models of a real human brain o Made to run the ship o Made very human conversations • Ender's Game series: Jane o Made from "philotic connection" o Human conversation
  • 11. Amity School of Engineering & Technology Problems of Human-Computer Dialogue • At the moment, most common computer dialogue systems (call systems, chatter bots, etc.) cannot handle arbitrary input o In many cases, the computer can only respond to "expected" speech o Call systems often compensate with "Sorry, I didn't get that," when something unexpected is said.
  • 12. Amity School of Engineering & Technology Problems of Human-Computer Dialogue • Computers need to be able to learn and process colloquial speech • Needed to understand informal speakers: o Understanding varied responses for call systems o Accounting for variations in spoken numbers • Processing colloquialisms is also necessary for seamless dialogue, where the computer must avoid sounding too formal o John Connor: "No, no, no, no. You gotta listen to the way people talk. You don't say 'affirmative,' or [stuff] like that. You say 'no problemo.' "
  • 13. Amity School of Engineering & Technology Successes of Human-Computer Dialogue • So far, human-computer dialogue has been most successful in applications where information about a specific topic is sought from the computer. o Electronic calling systems: company-specific o Travel agents: specific to an airline or destination • However, more complex systems of human-computer dialogue have been produced which can interpret more varied input. o Physics tutoring system (ITSPOKE) which can analyze and explain errors in the response to a physics problem. o Allows for more complex input than "Yes," "No," or "Flight UA-93" • These still cannot compare to true human-human dialogue.
  • 14. Amity School of Engineering & Technology Machine Translation • Important for: o accessing information in a foreign language o communication with speakers of other languages • The majority of documents on the world wide web are in languages other than English
  • 15. Amity School of Engineering & Technology Statistical Translation • Rule based • Works relatively well with large sets of data • Used probability to translate text • Natural translations • Google
  • 16. Amity School of Engineering & Technology Example Based Translation • Converts "parallel" lines of text between language • Only accurate for simple lines • Minimal pairs are easy • Analogy based
  • 17. Amity School of Engineering & Technology Paraphrasing • Takes words and makes them simpler automatically • For example in Spanish conjugated words like usado may be changed to usar
  • 18. Amity School of Engineering & Technology Future of Machine Translation • Goal: o Aim to be able to flawlessly translate languages • Link Human-Computer Dialogue and Machine Translation • Have someone be able to talk in one language to a computer, translate for another person • Translated Video Chat
  • 19. Amity School of Engineering & Technology Machine Translation in Fiction • Star Wars: C-3P0 o Interpreter o Could hear and translate alien languages o Final goal of machine translation • Star Trek: Universal Translator o Computer can seamlessly translate alien languages
  • 20. Amity School of Engineering & Technology Problems • Works well only with predictable texts. • Doesn't work well with domains where people want translation the most: o spontaneous conversations o in person o on the telephone o and on the Internet.
  • 21. Amity School of Engineering & Technology Problems • Computers can't deal with ambiguity, syntactic irregularity, multiple word meanings and the influence of context. Time flies like an arrow. Fruit flies like a banana. • Accurate translation requires an understanding of the text, situation, and a lot of facts about the world in general. The box is in the pen.
  • 22. Amity School of Engineering & Technology Problems • The sign is describing a restaurant (the Chinese text, 餐厅, means "dining hall"). • In the process of making the sign, the producers tried to translate Chinese text into English with a machine translation system, but the software didn't work, producing the error message, "Translation Server Error." • The software's user didn't know English and thought the error message was the translation.
  • 23. Amity School of Engineering & Technology Successes • Product knowledge bases need to be translated into multiple languages • Hiring a large multilingual support staff is expensive • Machine translation is cheaper and accurate with predictable texts. • Microsoft, Autodesk, Symantec, and Intel use it. o Makes customers happy o Still readable though slightly chunkier than human translations