A multidimensional approach to aligned sentences in translated text
| Autor: | Lidun Hareide, Gard B. Jenset |
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| Rok vydání: | 2013 |
| Předmět: |
Creative visualization
Computer science business.industry media_common.quotation_subject General Medicine Norwegian computer.software_genre language.human_language Linguistics Style (sociolinguistics) Parallel corpora lcsh:Philology. Linguistics lcsh:P1-1091 Bilingual corpus language Corpus based Artificial intelligence Unsupervised clustering business computer Sentence Natural language processing media_common |
| Zdroj: | Bergen Language and Linguistics Studies, Vol 3, Iss 1 (2013) |
| ISSN: | 1892-2449 |
| DOI: | 10.15845/bells.v3i1.356 |
| Popis: | Using unsupervised clustering techniques this study explores sentence alignment patterns in a parallel corpus of Norwegian source texts and Spanish translations, the NSPC (Hareide and Hofland 2012). The results show that three strategies with respect to sentence alignment dominate: one to one correspondence, merging two sentences into one, and removing sentences altogether (omission). The strategies are intricately correlated with the variables translator, author, and genre. However, we show how visualization techniques for cluster analyses offer a possibility for teasing apart these interactions as well as their relative importance. Our results indicate that non-fiction texts allow translators more freedom with respect to the treatment of sentences than do texts that are written by professional authors of fiction. The style of the author appears to play only a secondary role, but is especially important in fiction. Keywords: corpus based translation, cluster analysis, parallel corpora, corpus alignment, unidirectional bilingual corpus |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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