Inversion Transduction Grammar

. We present a new implication of Wu’s (1997) Inversion Transduction Grammar (ITG) Hypothesis, on the problem of retriev- ing truly parallel sentence translations from large collections of highly non-parallel …...

We present a version of Inversion Trans- duction Grammar where rule probabili- ties are lexicalized throughout the syn- chronous parse tree, along with pruning techniques for efficient training. Align- ment …...

We present a new method for learning to parse a bilingual sentence using Inversion Transduction Grammar trained on a parallel corpus and a monolingual treebank. The method produces a parse …...

We propose a version of Inversion Transduction Grammar (ITG) model with IBM-style notation of fertility to improve word-alignment performance. In our approach, binary context-free grammar rules of the source language, …...

While Inversion Transduction Grammar (ITG) has regained more and more attention in recent years, it still suffers from the major obstacle of speed. We propose a discriminative ITG prun- ing …...

This paper proposes cross-lingual language modeling for transcribing source resource- poor languages and translating them into tar- get resource-rich languages if necessary. Our focus is to improve the speech recognition …...

AbstractPrevious attempts at injecting semantic frame biases into SMT training for low resource languages failed because either (a) no semantic parser is available for the low resource input language; or …...