We propose a number of refinements to the canonical approach to interactive translation prediction. By more permissive matching criteria, placing emphasis on matching the last word of the user prefix, and dealing with predictions to partially typed words, we observe gains in both word prediction accuracy (+5.4%) and letter prediction accuracy (+9.3%).
This approach was recently refined with more permissive matching criteria by REF , who report strong improvements in prediction accuracy.
Refinements to Interactive Translation Prediction Based on Search Graphs
ACL
Computer Science