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Natural Language Processing - Coggle Diagram
Natural Language Processing
Formal and Natural language
Formal Language
Formal language in computer science is made up of tokens, symbols, and etters that are drawn from the alphabet. These words follow a certain set of guidelines in their formation. For example, programming languages
Natural Language
To put it simply, human language is used for communication. This indicates that human languages are referred to as natural languages. Ex: Sinhala, English, and Spanish
Main points to concern in NLP
Focuses on formal, structural models of language and the identification of universals in language
Computer science is the study of creating internal data representations and processing these structures effectively.
Cognitive psychology aims to represent language use in a psychologically reasonable manner by using language usage as a window into human cognitive processes.
Morphology
Internal structure of words and forms is called morphology
Lexicon
Understanding everything about each word involves comprehending its meaning, its part of speech, and its relationship to other words in a sentence.
What is language
simply, a language is a primary medium to connect two parties.
NPL
The ability of a computer to understand human language as it is spoken and written is known as natural language processing (NLP).
Phonology
Sound patterns that occur within languages are referred to as phonology. These sound patterns can provide significant clues about the meaning of a word or a sentence.
Phonetics
How humans produce and perceive sounds, or in the case of sign languages, the equivalent aspects of sign.
History
1950s (Turing Test)
1952 (Hodgkin-Huxley model and Al inspiration)
1957 (Professor Noam Chomsky revolutionized previous linguistics concepts)
1958 - 1966 (Al and NLP research was considered to be dead by many people)
1980s (NLP Revolution - increased computational power -Machine Learning "ML' Algorithms)
2000s (Research increased its focus on semi-supervised, and unsupervised machine learning algorithms)
2010s - present (Deep Leering achieved state-of-he-art performance)
Applications
Chatbots (Neomi, at Spoke)
Text Summarization
(paraphraser.io)
Email Filtering
Social Media Monitoring
Targeted Advertising
Voice Assistants (Siri, Google assistant)
Grammar Checkers (Grammarly)