A Statistical Translation Approach by Network Model

I present a translation approach based on a phrase-based maximum entropy model. To improve search performance, a beam search algorithm is exploited where the selection of the phrase candidate translation, the future probability calculation, and the pruning strategy are included. A neural network model with words and phrases is used. I obtain better translation results by the extensive experiments conducted on the real and synthetic datasets.