Machine translation is one of the most recent success stories of NLU. The goal of this problem is to take a text sentence in a source language, such as English and convert it into the same sentence in a given target language, such as Spanish. Traditional methods of solving this problem relied on using phrase-based models. These models typically chunk the sentences into shorter phrases and translate each of these phrases one by one into a target language phrase.
Though translation at phrase-level works reasonably well, when you combine these translated phrases into the target language to generate a fully translated sentence, you find occasional choppiness, or disfluency. To avoid this limitation of phrase-based machine ...
