Phrase linguistic classification and generalization for improving statistical machine translation

In this paper a method to incorporate linguistic information regarding single-word and compound verbs is proposed, as a first step towards an SMT model based on linguistically-classified phrases. By substituting these verb structures by the base form of the head verb, we achieve a better statistical word alignment performance, and are able to better estimate the translation model and generalize to unseen verb forms during translation. Preliminary experiments for the English - Spanish language pair are performed, and future research lines are detailed. © 2005 Association for Computational Linguistics.

Computational study of viscous effects on lobed mixer flow features and performance

This article describes a computational study of viscous effects on lobed mixer flowfields. The computations, which were carried out using a compressible, three-dimensional, unstructured-mesh Navier-Stokes solver, were aimed at assessing the impacts on mixer performance of inlet boundary-layer thickness and boundary-layer separation within the lobe. The geometries analyzed represent a class of lobed mixer configurations used in turbofan engines. Parameters investigated included lobe penetration angles from 22 to 45 deg, stream-to-stream velocity ratios from 0.5 to 1.0, and two inlet boundary-layer displacement thicknesses. The results show quantitatively the increasing influence of viscous effects as lobe penetration angle is increased. It is shown that the simple estimate of shed circulation given by Skebe et al. (Experimental Investigation of Three-Dimensional Forced Mixer Lobe Flow Field, AIAA Paper 88-3785, July, 1988) can be extended even to situations in which the flow is separated, provided an effective mixer exit angle and height are defined. An examination of different loss sources is also carried out to illustrate the relative contributions of mixing loss and of boundary-layer viscous effects in cases of practical interest.