A new machine translation approach using multiple translation engines and sentence partitioning

Abstract

In this paper, we present a new machine translation (MT) approach using MT engines and sentence partitioning. A multiple engine MT system consists of several MT engines running in parallel, coordinated by a controller. Each engine is implemented using an existing MT technique and has its own characteristics. When translating a sentence, each engine translates it independently. If more than one engine translates the sentence successfully, the controller chooses the best translation according to a combining algorithm implemented using translation statistics. If no engine succeeds in translating the sentence, the, controller partitions the sentence, coordinates the engines to translates its constituent simple sentences, and combines the partial translation results into a translation result for the whole input sentence. A complex sentence is partitioned based on conjunctives and punctuation marks such as comma: and semicolon. We have developed a multiple engine MT system based on the above approach. The system consists of four independent MT engines. The experiments show that the proposed approach is effective for implementing practical MT systems.