On the differences between human translations
Many studies have confirmed that translated texts exhibit different features than texts originally written in the given language. This work explores texts translated by different translators taking into account expertise and native language. A set of computational analyses was conducted on three language pairs, English-Croatian, German-French and English-Finnish, and the results show that each of the factors has certain influence on the features of the translated texts, especially on sentence length and lexical richness. The results also indicate that for translations used for machine translation evaluation, it is important to specify these factors, especially if comparing machine translation quality with human translation quality is involved.
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationSentenceTranslationSimilar Papers 제목 키워드 기반
DiHuTra: a Parallel Corpus to Analyse Differences between Human Translations
This project aimed to design a corpus of parallel human translations (HTs) of the same source texts by professionals and students. The resulting corpus consists of English news and reviews source texts, their translation…
Machine TranslationTranslationComparing Formulaic Language in Human and Machine Translation: Insight from a Parliamentary Corpus
A recent study has shown that, compared to human translations, neural machine translations contain more strongly-associated formulaic sequences made of relatively high-frequency words, but far less strongly-associated fo…
ArticlesMachine TranslationTranslationTrain, Sort, Explain: Learning to Diagnose Translation Models
Evaluating translation models is a trade-off between effort and detail. On the one end of the spectrum there are automatic count-based methods such as BLEU, on the other end linguistic evaluations by humans, which arguab…
TranslationDecoding and Diversity in Machine Translation
Neural Machine Translation (NMT) systems are typically evaluated using automated metrics that assess the agreement between generated translations and ground truth candidates. To improve systems with respect to these metr…
DiversityMachine TranslationNMTTranslationMan vs. Machine: Extracting Character Networks from Human and Machine Translations
Most of the work on Character Networks to date is limited to monolingual texts. Conversely, in this paper we apply and analyze Character Networks on both source texts (English novels) and their Finnish translations (both…