Jonathan Graehl

2 paper cards in Mova's library · 2004–2006

Jonathan Graehl wrote 2 of the papers Mova reads, in 2004–2006, most of them on Machine translation; often with Kevin Knight, Daniel Marcu, Ignacio Thayer.

The profile is the library's match of the name; two people with one name are not always told apart.

Papers

Scalable Inference and Training of Context-Rich Syntactic Translation Models (2006)
The paper extends the rule extraction of Galley et al. (2004). Instead of keeping one minimal derivation per sentence pair, it builds a forest of many derivations, so that larger rules with more syntactic context and alternative readings of unaligned words are all available. It puts probabilities on these multi-level…
Training Tree Transducers (2004)
The paper argues that probabilistic models of language should be written as tree transducers, since the theory of tree automata is well developed and gives tools that string models have.