Recent research on multilingual statistical machine translation focuses on the usage of pivot languages in order to overcome resource limitations for certain language pairs. This paper provides new insights into what factors make a good pivot language and investigates the impact of these factors on the overall pivot translation performance. Pivot-based SMT experiments translating between 22 IndoEuropean and Asian languages were used to analyze the impact of eight factors (language family, vocabulary, sentence length, language perplexity, translation model entropy, reordering, monotonicity, engine performance) on pivot translation performance. The results showed that 81% of system performance variations can be explained by these factors.
['Michael Paul', 'Eiichiro Sumita']
Translation Quality Indicators for Pivot-based Statistical MT