The State of Machine Translation in 1996

Progress in MT research has been painfully slow, and the ultimate goal has kept on receding with each step forward. Traditional rule-based approaches (whether of the linguistics-based or the knowledge-based variety) have resulted in systems that tend to collapse under the weight of their own complexity well before they rise above the clouds of semantical ambiguity. Recent results in corpus-based approaches (whether of the statistical [2] or the example-based variety) indicate that it may soon become possible to develop systems that match the performance of the best rule-based systems with substantially less human labour; but these results do not appear to bring us much closer to high-accuracy MT.