This week we discussed how standard machine translation techniques can be adapted in order to give output in metered, rhymed, or otherwise constrained form. There were two papers directly on this subject: the focus paper and the paper Dong and I read. We decided that the focus paper did not use particularly interesting modelling, nor did it really demonstrate that its results were interesting. The other paper also suffered from a lack of good evaluation, but it used a richer model that made significantly fewer assumptions about the problem.
Although the task of translating into to metered verse is not a particularly useful task on its own, there are potentially other similar tasks that could be quite useful. In our discussion, we thought about translating between technical and non-technical text, producing more easily memorizable text, and applications to marketing. We also had a brief discussion about the history of phrase-based MT, but did not really conclude anything.