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Conference Papers Year : 2006

Soft Uncoupling of Markov Chains for Permeable Language Distinction: A New Algorithm

Abstract

Without prior knowledge, distinguishing different languages may be a hard task, especially when their borders are permeable. We develop an extension of spectral clustering -- a powerful unsupervised classification toolbox -- that is shown to resolve accurately the task of soft language distinction. At the heart of our approach, we replace the usual hard membership assignment of spectral clustering by a soft, probabilistic assignment, which also presents the advantage to bypass a well-known complexity bottleneck of the method. Furthermore, our approach relies on a novel, convenient construction of a Markov chain out of a corpus. Extensive experiments with a readily available system clearly display the potential of the method, which brings a visually appealing soft distinction of languages that may define altogether a whole corpus.

Dates and versions

hal-00327782 , version 1 (09-10-2008)

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Richard Nock, Pascal Vaillant, Frank Nielsen, Claudia Henry. Soft Uncoupling of Markov Chains for Permeable Language Distinction: A New Algorithm. 17th European Conference on Artificial Intelligence (ECAI 2006), Aug 2006, Riva del Garda, Italy. ISBN 1-58603-642-3, p. 823-824. ⟨hal-00327782⟩

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