Measure Word Generation for English-Chinese SMT Systems

Measure words in Chinese are used to indicate the count of nouns. Conventional statistical machine translation (SMT) systems do not perform well on measure word generation due to data sparseness and the potential long distance dependency between measure words and their corresponding head words. In this paper, we propose a statistical model to generate appropriate measure words of nouns for an English-to-Chinese SMT system. We model the probability of measure word generation by utilizing lexical and syntactic knowledge from both source and target sentences. Our model works as a post-processing procedure over output of statistical machine translation systems, and can work with any SMT system. Experimental results show our method can achieve high precision and recall in measure word generation.