NLP

Language and Vision

Motivation Human interacts with environment multimodal Modalities Text Audio Vision Other modalities can be used to disambiguate text Jointly using different modalities Image description Generation Generate description/caption of image Verbalize the most salient aspects of the image

2020-09-20

Information Retrieval

Overview Information Retrieval (IR): finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within large collections (usually stored on computers). Use case / applications

2020-09-20

Dialog Management

Dialog Modeling Dialog manager Manage flow of conversation Input: Semantic representation of the input Output: Semantic representation of the output Utilize additional knowledge User information Dialog History Task-specific information

2020-09-20

Natural Language Generation

Motivation ๐ŸŽฏ Goal: generate natural language from semantic representation (or other data) Examples Pollen Forecast Pollen Forecast for Scotland Taking six numbers as input, a simple NLG system generates a short textual summary of pollen levels

2020-09-19

Natural/Spoken Language Understanding

Definition Natural language understanding Representing the semantics of natural language Possible view: Translation from natural language to representation of meaning Difficulties Ambiguities Lexical Syntax Referential Vagueness E.g., โ€œI had a late lunch.

2020-09-18

Question Answering

Definition Question Answering Automatically answer questions posed by humans in natural language Give user short answer to their question Gather and consult necessary information Related topics Information Retrieval Reading Comprehension

2020-09-18

Summarization

TL;DR Text summarization Most important technique Extraction Tasks: Key word extraction Sentence extraction Algorithms: Supervised Unsupervised Abstract summarization still an open problem Introduction What is Summarization? Reduce natural language text document Goal: Compress text by extracting the most important/relevant parts ๐Ÿ’ช Applications Articles, news: Outlines or abstracts

2020-09-16

Parsing

TL;DR Representing and Analyze Sentence Structure Phrase structure grammar Context free grammar Problems: Ambiguities : PP Attachment Traditional Approaches Stochastically Parsing Probabilistic Context Free Grammar CYK Algorithm Transition-based parsing

2020-09-15

Named Entity Recognition

Introduction Definition Named Entity: some entity represented by a name Named Entity Recognition: Find and classify named entities in text Why useful? Create indices & hyperlinks Information extraction Establish relationships between named entities, build knowledge base Question answering: answers often NEs

2020-09-15

Part-of-Speech Tagging

Part-of-Speech Tagging What is Part-of-Speech Tagging? Part-of-Speech tagging: Grammatical tagging Word-category disambiguation Task: Marking up a word in a text as corresponding to a particular part of speech based on definition and context Word level task: Assign one class to every word

2020-09-15