This document discusses natural language processing (NLP) and how computers can be programmed to understand and communicate with humans using natural human languages like humans do. It covers how humans communicate with each other using languages and how computer systems try to replicate this ability. It then describes some common applications of NLP like speech recognition, sentiment analysis, machine translation and chatbots. It also discusses two key aspects of NLP - natural language understanding (NLU) which involves understanding what users say and their intent, and natural language generation (NLG) which is about generating intelligent conversational responses for users.

1. NATURAL
LANGUAGE
PROCESSING
(NLP)
ZAHEEN BANO COURSE – LECTURE
SERIES

2. HOW HUMAN COMMUNICATE WITH EACH
OTHER
Use natural language
I Use multiple language
English
Urdu
Punjabi
You ; interpreting – understand – reply
I understand
Human behavior become intelligent

3. COMPUTER SHOULD REPLICATE THE SAME
THING
Copy the same
Computer interact with
Machine
Human
Implement the same human rules

4. APPLICATIONS OF NLP
• Speech Recognition
• Widely used
• Google Assistant | Siri by Apple
• Valid Reply
• Sentimental Analysis
• Social Media | Tweet Analysis | Positive, Negative and Neutral
• Machine Translations
• Interpreter - Traditional
• Google Translation
• Validity increased
• Chat Bots
• EBay catboats
• Knowledge based reply

5. NLP MODEL
Speech
Recognition
Natural
Language
Understanding
Natural
Language
Generation
NLU NL
G

6. NLU : WHAT DO THE USER
SAY?
THEIR INTENT?
MEANING?
Challenges
•Lexical Ambiguity | The Tank was full
of water
•Syntactic Ambiguity | Old men and
women were take to safe place
•Semantic Ambiguity | The Car hit the
cycle while it was moving
•Pragmatic Ambiguity | The Police is
coming

7. NATURAL LANGUAGE
GENERATION (NLG)
• What should we say to user?
• It should be intelligent and conversational
• Text and Sentence Planning
• Deal with structured data
CORPUS