Publication

Investigating Lexical Substitution Scoring for Subtitle Generation

2006
Conference Papers

Abstract

This paper investigates an isolated setting of the lexical substitution task of replacing words with their synonyms. In particular, we examine this problem in the setting of subtitle generation and evaluate state of the art scoring methods that predict the validity of a given substitution. The paper evaluates two context independent models and two contextual models. The major findings suggest that distributional similarity provides a useful complementary estimate for the likelihood that two Wordnet synonyms are indeed substitutable, while proper modeling of contextual constraints is still a challenging task for future research.

Official source

https://infoscience.epfl.ch/entities/publication/836bec96-b7c3-4332-9362-d169cc070a02

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2006
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/836bec96-b7c3-4332-9362-d169cc070a02

About this result

Related concepts (27)

WordNet

WordNet is a lexical database of semantic relations between words that links words into semantic relations including synonyms, hyponyms, and meronyms. The synonyms are grouped into synsets with short definitions and usage examples. It can thus be seen as a combination and extension of a dictionary and thesaurus. While it is accessible to human users via a web browser, its primary use is in automatic text analysis and artificial intelligence applications.

Synonym

A synonym is a word, morpheme, or phrase that means exactly or nearly the same as another word, morpheme, or phrase in a given language. For example, in the English language, the words begin, start, commence, and initiate are all synonyms of one another: they are synonymous. The standard test for synonymy is substitution: one form can be replaced by another in a sentence without changing its meaning. Words are considered synonymous in only one particular sense: for example, long and extended in the context long time or extended time are synonymous, but long cannot be used in the phrase extended family.

BabelNet

BabelNet is a multilingual lexicalized semantic network and ontology developed at the NLP group of the Sapienza University of Rome. BabelNet was automatically created by linking Wikipedia to the most popular computational lexicon of the English language, WordNet. The integration is done using an automatic mapping and by filling in lexical gaps in resource-poor languages by using statistical machine translation. The result is an encyclopedic dictionary that provides concepts and named entities lexicalized in many languages and connected with large amounts of semantic relations.

Related publications (1)

Investigating Lexical Substitution Scoring for Subtitle Generation

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