Automatic Sentence Simplification for Subtitling in Dutch and English

We describe ongoing work on sentence summarization in the European MUSA project and the Flemish ATraNoS project. Both projects aim at automatic generation of TV subtitles for hearing-impaired people. This involves speech recognition, a topic which is not covered in this paper, and summarizing sentences in such a way that they fit in the available space for subtitles. The target language is equal to the source language: Dutch in ATraNoS and English in MUSA. A separate part of MUSA deals with translating the English subtitles to French and Greek. We compare two methods for monolingual sentence length reduction: one based on learning sentence reduction from a parallel corpus and one based on hand-crafted deletion rules

Reduction of Dutch Sentences for Automatic Subtitling

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