Reduction of Dutch Sentences for Automatic Subtitling

E.F. Tjong Kim Sang; W. Daelemans; A. Höthker

Reduction of Dutch Sentences for Automatic Subtitling

E.F. Tjong Kim Sang, W. Daelemans, A. Höthker

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

We compare machine learning approaches for sentence length reduction for automatic generation of subtitles for deaf and hearing-impaired people with a method which relies on hand-crafted deletion rules. We describe building the necessary resources for this task: a parallel corpus of examples of news broadcasts of the Flemish VRT broadcasting corporation, and a Dutch shallow parser based on the material of the Spoken Dutch Corpus (CGN). We evaluate the sentence simplifiers and discuss their performance

Original language	English
Title of host publication	Proceedings of CLIN-2003
Place of Publication	Antwerp
Publisher	Unknown Publisher
Pages	109-123
Number of pages	15
Publication status	Published - 2004

Cite this

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title = "Reduction of Dutch Sentences for Automatic Subtitling",

abstract = "We compare machine learning approaches for sentence length reduction for automatic generation of subtitles for deaf and hearing-impaired people with a method which relies on hand-crafted deletion rules. We describe building the necessary resources for this task: a parallel corpus of examples of news broadcasts of the Flemish VRT broadcasting corporation, and a Dutch shallow parser based on the material of the Spoken Dutch Corpus (CGN). We evaluate the sentence simplifiers and discuss their performance",

author = "\{Tjong Kim Sang\}, E.F. and W. Daelemans and A. H{\"o}thker",

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year = "2004",

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T1 - Reduction of Dutch Sentences for Automatic Subtitling

AU - Tjong Kim Sang, E.F.

AU - Daelemans, W.

AU - Höthker, A.

N1 - Pagination: 15

PY - 2004

Y1 - 2004

N2 - We compare machine learning approaches for sentence length reduction for automatic generation of subtitles for deaf and hearing-impaired people with a method which relies on hand-crafted deletion rules. We describe building the necessary resources for this task: a parallel corpus of examples of news broadcasts of the Flemish VRT broadcasting corporation, and a Dutch shallow parser based on the material of the Spoken Dutch Corpus (CGN). We evaluate the sentence simplifiers and discuss their performance

AB - We compare machine learning approaches for sentence length reduction for automatic generation of subtitles for deaf and hearing-impaired people with a method which relies on hand-crafted deletion rules. We describe building the necessary resources for this task: a parallel corpus of examples of news broadcasts of the Flemish VRT broadcasting corporation, and a Dutch shallow parser based on the material of the Spoken Dutch Corpus (CGN). We evaluate the sentence simplifiers and discuss their performance

M3 - Conference contribution

SP - 109

EP - 123

BT - Proceedings of CLIN-2003

PB - Unknown Publisher

CY - Antwerp

ER -

Reduction of Dutch Sentences for Automatic Subtitling

Abstract

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