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Conference Papers Year : 2012

Comparing performance of different set-covering strategies for linguistic content optimization in speech corpora

Nelly Barbot
Olivier Boëffard
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Arnaud Delhay

Abstract

Set covering algorithms are efficient tools for solving an optimal linguistic corpus reduction. The optimality of such a process is directly related to the descriptive features of the sentences of a reference corpus. This article suggests to verify experimentally the behaviour of three algorithms, a greedy approach and a lagrangian relaxation based one giving importance to rare events and a third one considering the Kullback-Liebler divergence between a reference and the ongoing distribution of events. The analysis of the content of the reduced corpora shows that the both first approaches stay the most effective to compress a corpus while guaranteeing a minimal content. The variant which minimises the Kullback-Liebler divergence guarantees a distribution of events close to a reference distribution as expected; however, the price for this solution is a much more important corpus. In the proposed experiments, we have also evaluated a mixed-approach considering a random complement to the smallest coverings.
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Dates and versions

hal-00784377 , version 1 (04-02-2013)

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  • HAL Id : hal-00784377 , version 1

Cite

Nelly Barbot, Olivier Boëffard, Arnaud Delhay. Comparing performance of different set-covering strategies for linguistic content optimization in speech corpora. International Conference on Language Resources and Evaluation (LREC'12), May 2012, Istanbul, Turkey. ⟨hal-00784377⟩
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