Abstract | On top of the pruning framework, we also propose a discriminative ITG alignment model using hierarchical phrase pairs, which improves both F-score and Bleu score over the baseline alignment system of GIZA++. |
Evaluation | IBM Model 1 and HMM alignment model are re-implemented as they are required by the three ITG pruning methods. |
Introduction | (2009) do pruning based on the probabilities of links from a simpler alignment model (viz. |
The DPDI Framework | The simpler alignment model we used is HMM. |
The DPDI Framework | The four links are produced by some simpler alignment model like HMM. |
The DPDI Framework | f len +elen Where #linksincon is the number of links which are inconsistent with the phrase pair according to some simpler alignment model (e.g. |
Experiments | This task highlights the evolution and alignment models . |
Introduction | Finally, an alignment model maps the flat word lists to cognate groups. |
Introduction | Inference requires a combination of message-passing in the evolutionary model and iterative bipartite graph matching in the alignment model . |
Background | The following constraints on links are assumed by some or all alignment models: |
Background | We refer to an alignment model that assumes all three constraints as a pure one-to-one (ll) model. |
Extrinsic evaluation | The TiMBL L2P generation method (Table 2) is applicable only to the 1-1 alignment models . |
Experiments | We align the same core subset with our trained hypergraph alignment model , and extract a second set of translation rules. |
Introduction | Generative alignment models like IBM Model-4 (Brown et al., 1993) have been in wide use for over 15 years, and while not perfect (see Figure 1), they are completely unsupervised, requiring no annotated training data to learn alignments that have powered many current state-of-the-art translation system. |
Introduction | We present in this paper a discriminative alignment model trained on relatively little data, with a simple, yet powerful hierarchical search procedure. |
Substructure Spaces for BTKs | 5 Alignment Model |
Substructure Spaces for BTKs | Given feature spaces defined in the last two sections, we propose a 2-phase subtree alignment model as follows: |
Substructure Spaces for BTKs | In order to evaluate the effectiveness of the alignment model and its capability in the applications requiring syntactic translational equivalences, we employ two corpora to carry out the subtree alignment evaluation. |