Abstract
This paper introduces a domain-adapted word segmentation approach to text where a word delimiter is not used regularly. It depends on an unknown word extraction technique. This approach is essential for language modeling to adapt to new domains since a vocabulary set is activated in a word segmentation step. We have achieved ERR 21.22% in Korean word segmentation. In addition, we show that an incremental domain adaptation of the word segmentation decreases the perplexity of input text gradually. It means that our approach supports an out-of-domain language modeling.
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Chung, E., Jeon, HB., Park, JG., Lee, YK. (2011). Domain-Adapted Word Segmentation for an Out-of-Domain Language Modeling. In: Delgado, RC., Kobayashi, T. (eds) Proceedings of the Paralinguistic Information and its Integration in Spoken Dialogue Systems Workshop. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1335-6_9
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DOI: https://doi.org/10.1007/978-1-4614-1335-6_9
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