Translation Quality Indicators for Pivot-based Statistical MT
Michael D. Paul, Eiichiro Sumita · 2011
Recent research on multilingual statisti-cal machine translation focuses on the us-age of pivot languages in order to over-come resource limitations for certain lan-guage pairs. This paper provides new in-sights into what factors make a good pivot language and investigates the impact of these factors on the overall pivot transla-tion performance. Pivot-based SMT ex-periments translating between 22 Indo-European and Asian languages were used to analyze the impact of eight factors (lan-guage family, vocabulary, sentence length, language perplexity, translation model en-tropy, reordering, monotonicity, engine performance) on pivot translation perfor-mance. The results showed that 81 % of system performance variations can be ex-plained by these factors. 1