Tracing Source Language Interference in Translation with Graph-Isomorphism Measures
Previous research has used linguistic features to show that translations exhibit traces of source language interference and that phylogenetic trees between languages can be reconstructed from the results of translations into the same language. Recent research has shown that instances of translationese (source language interference) can even be detected in embedding spaces, comparing embeddings spaces of original language data with embedding spaces resulting from translations into the same language, using a simple Eigenvector-based divergence from isomorphism measure. To date, it remains an open question whether alternative graph-isomorphism measures can produce better results. In this paper, we (i) explore Gromov-Hausdorff distance, (ii) present a novel spectral version of the Eigenvector-based method, and (iii) evaluate all approaches against a broad linguistic typological database (URIEL). We show that language distances resulting from our spectral isomorphism approaches can reproduce genetic trees on a par with previous work without requiring any explicit linguistic information and that the results can be extended to non-Indo-European languages. Finally, we show that the methods are robust under a variety of modeling conditions.
Code (0)
등록된 구현이 없습니다.
Tasks
Open-Ended Question AnsweringTranslationSimilar Papers 제목 키워드 기반
HLT-MT: High-resource Language-specific Training for Multilingual Neural Machine Translation
Multilingual neural machine translation (MNMT) trained in multiple language pairs has attracted considerable attention due to fewer model parameters and lower training costs by sharing knowledge among multiple languages.…
DecoderMachine TranslationTranslationCauses and Cures for Interference in Multilingual Translation
Multilingual machine translation models can benefit from synergy between different language pairs, but also suffer from interference. While there is a growing number of sophisticated methods that aim to eliminate interfe…
Machine TranslationTranslationFound in Translation: Reconstructing Phylogenetic Language Trees from Translations
Translation has played an important role in trade, law, commerce, politics, and literature for thousands of years. Translators have always tried to be invisible; ideal translations should look as if they were written ori…
TranslationLearning Language Specific Sub-network for Multilingual Machine Translation
Multilingual neural machine translation aims at learning a single translation model for multiple languages. These jointly trained models often suffer from performance degradation on rich-resource language pairs. We attri…
AttributeMachine TranslationTranslationPost-editese: an Exacerbated Translationese
Post-editing (PE) machine translation (MT) is widely used for dissemination because it leads to higher productivity than human translation from scratch (HT). In addition, PE translations are found to be of equal or bette…
Machine TranslationTranslation