An Investigation on the Effectiveness of Features for Translation Quality Estimation

Kashif Shah, Trevor Conn, Lucia Specia
2013 Machine Translation Summit  
We describe a systematic analysis on the effectiveness of features commonly exploited for the problem of predicting machine translation quality. Using a feature selection technique based on Gaussian Processes, we identify small subsets of features that perform well across many datasets for different language pairs, text domains, machine translation systems and quality labels. In addition, we show the potential of the reduced feature sets resulting from our feature selection technique to lead to
more » ... significantly better performance in most datasets, as compared to the complete feature sets.
dblp:conf/mtsummit/ShahCS13 fatcat:wxx7ynyfq5ghhahc365hsco7tm