Natural Language Processing (NLP)
Machine Learning
The processing of any natural language in order to understand both its grammatical syntax and semantics
Natural Language
Any language that has evolved naturally in humans (as opposed to constructed and formal languages for computers or logic)
Categories of NLP
Syntax-related
Parsing grammar
Grammar induction
Word and sentence breaking / segmentation / boundary disambiguation
Part-of-speech tagging (e.g. as nouns, verbs etc)
Terminology extraction (finding relevant terms in a corpus)
Semantic-related
Language translation
Lexical semantics & word-sense disambiguation (identifying the correct meaning of the words in the given context)
Named entity recognition (identification and understanding of proper names/people/places)
Generation of natural language
Optical Character Recognition (OCR)
Question answering
Relationship extraction (identifying and understanding relationships among named entities)
Sentiment analysis / opinion mining (identifying, extracting and quantifying emotional states, polarised opinions and subjective information). Text-based or multi-modal with audio and visual data.
Topic segmentation / classification (identifying the topic of chunks of the corpus)
Discourse-related
Summary generation (producing a summary of a corpus)
Co-reference resolution (determining which words refer to the same thing - e.g. when there are two or more nouns mentioned, which does a pronoun refer to?)
Discourse analysis (e.g. identifying connected parts of text or speech acts - such as conversation questions and answers, statements, assertiongs)
Speech-related
Speech-to-Text / speech recognition
Text-to-Speech