Sentence Compression for Automated Subtitling: A Hybrid Approach
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TL;DR
This paper describes how an input sentence gets analysed by using a.o. a tagger, a shallow parser and a subordinate clause detector, and how, based on this analysis, several compressed versions of this sentence are generated, each with an associated estimated probability.
Abstract
In this paper a sentence compression tool is described. We describe how an input sentence gets analysed by using a.o. a tagger, a shallow parser and a subordinate clause detector, and how, based on this analysis, several compressed versions of this sentence are generated, each with an associated estimated probability. These probabilities were estimated from a parallel transcript/subtitle corpus. To avoid ungrammatical sentences, the tool also makes use of a number of rules. The evaluation was done on three different pronunciation speeds, averaging sentence reduction rates of 40 % to 17%. The number of reasonable reductions ranges between 32.9% and 51%, depending on the average estimated pronunciation speed.