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Natural Language
Processing
INTRODUCTION
• What is Natural Language Processing
• NLP for machines
• Why NLP
• History of NLP
3
What is natural language
processing?
• Process information contained in natural
language text
• Also known as Computational Linguistics (CL),
Human Language Technology (HLT), Natural
Language Engineering (NLE)
4
NLP for machines…
• Analyze, understand and generate human languages just like
humans do
• Applying computational techniques to language domain
• To explain linguistic theories, to use the theories to build
systems that can be of social use
• Started off as a branch of Artificial Intelligence
• Borrows from Linguistics, Psycholinguistics, Cognitive Science
& Statistics
• Make computers learn our language rather than we learn
theirs 5
Why NLP?
• A hallmark of human intelligence
• Text is the largest repository of human knowledge and is
growing quickly
• computer programmes that understood text or speech
6
Components of NLP
• Natural Language Understanding
• Taking some spoken/typed sentence and working out what it
means
• Natural Language Generation
• Taking some formal representation of what you want to say and
working out a way to express it in a natural (human) language
(e.g., English)
9
Components of NLP (cont.)
• Natural Language Understanding
• Mapping the given input in the natural language into a useful
representation
• Different level of analysis required:
• morphological analysis
• syntactic analysis
• semantic analysis
• discourse analysis
10
Components of NLP (cont.)
• Natural Language Generation
• Producing output in the natural language from some internal
representation
• Different level of synthesis required:
• deep planning (what to say)
• syntactic generation
• NL Understanding is much harder than NL Generation.
But, still both of them are hard
11
Steps of NLP
13
Morphological and Lexical Analysis
Syntactic Analysis
Semantic Analysis
Discourse Integration
Pragmatic Analysis
Natural Language Processing: A Guide to NLP

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Natural Language Processing: A Guide to NLP

  • 2. INTRODUCTION • What is Natural Language Processing • NLP for machines • Why NLP • History of NLP 3
  • 3. What is natural language processing? • Process information contained in natural language text • Also known as Computational Linguistics (CL), Human Language Technology (HLT), Natural Language Engineering (NLE) 4
  • 4. NLP for machines… • Analyze, understand and generate human languages just like humans do • Applying computational techniques to language domain • To explain linguistic theories, to use the theories to build systems that can be of social use • Started off as a branch of Artificial Intelligence • Borrows from Linguistics, Psycholinguistics, Cognitive Science & Statistics • Make computers learn our language rather than we learn theirs 5
  • 5. Why NLP? • A hallmark of human intelligence • Text is the largest repository of human knowledge and is growing quickly • computer programmes that understood text or speech 6
  • 6. Components of NLP • Natural Language Understanding • Taking some spoken/typed sentence and working out what it means • Natural Language Generation • Taking some formal representation of what you want to say and working out a way to express it in a natural (human) language (e.g., English) 9
  • 7. Components of NLP (cont.) • Natural Language Understanding • Mapping the given input in the natural language into a useful representation • Different level of analysis required: • morphological analysis • syntactic analysis • semantic analysis • discourse analysis 10
  • 8. Components of NLP (cont.) • Natural Language Generation • Producing output in the natural language from some internal representation • Different level of synthesis required: • deep planning (what to say) • syntactic generation • NL Understanding is much harder than NL Generation. But, still both of them are hard 11
  • 9. Steps of NLP 13 Morphological and Lexical Analysis Syntactic Analysis Semantic Analysis Discourse Integration Pragmatic Analysis