Comparison of Generation Strategies for Interactive Machine Translation

Abstract. Fully automatic translations are far from being perfect. Non-grammatical sentences are often produced by automatic systems and there is even no guarantee that the meaning of the sentence is preserved. Nevertheless, automatic translation systems can be used to help human translators to produce high-quality translations. This is the goal of the TransType2 project, where an interactive translation tool is being developed that suggests, in real time, possible completions for the sentences that the human translator is typing. This leads to a modification of the generation strategy of the translation system, as now we are looking for the best translation of the given source sentence that is compatible with the prefix. In order to remain within the tight response time constraints of such a system, some simplifications have to be done. In this paper, we review possible generation strategies for an interactive statistical machine translation system and analyze what is the loss in performance when strict time constraints have to be met. Experiments are performed on the Spanish-English and German-English Xerox corpora, which consist of the translation of technical manuals, and the results show that the real time generation strategy causes only a small performance degradation.