6533b7d5fe1ef96bd1264527

RESEARCH PRODUCT

Combining Machine Translated Sentence Chunks from Multiple MT Systems

Matīss RiktersInguna Skadiņa

subject

060201 languages & linguisticsParsingPerplexityPhraseMachine translationComputer sciencebusiness.industry06 humanities and the arts02 engineering and technologyHybrid machine translationcomputer.software_genre0602 languages and literatureChunking (psychology)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingLanguage modelArtificial intelligencebusinesscomputerNatural language processingSentence

description

This paper presents a hybrid machine translation (HMT) system that pursues syntactic analysis to acquire phrases of source sentences, translates the phrases using multiple online machine translation (MT) system application program interfaces (APIs) and generates output by combining translated chunks to obtain the best possible translation. The aim of this study is to improve translation quality of English – Latvian texts over each of the individual MT APIs. The selection of the best translation hypothesis is done by calculating the perplexity for each hypothesis using an n-gram language model. The result is a phrase-based multi-system machine translation system that allows to improve MT output compared to individual online MT systems. The proposed approach show improvement up to +1.48 points in BLEU and −0.015 in TER scores compared to the baselines and related research.

yearjournalcountryeditionlanguage
2018-01-01
https://doi.org/10.1007/978-3-319-75487-1_3