TransBooster: boosting the performance of wide-coverage machine translation systems

We propose the design, implementation and evaluation of a novel and modular approach to boost the translation performance of existing, wide-coverage, freely available machine translation systems based on reliable and fast automatic decomposition of the translation input and corresponding composition of translation output. We provide details of our method, and experimental results compared to the MT systems SYSTRAN and Logomedia. While many avenues for further experimentation remain, to date we fall just behind the baseline systems on the full 800-sentence testset, but in certain cases our method causes the translation quality obtained via the MT systems to improve