Multi-Target Machine Translation with Multi-Synchronous Context-free Grammars
نویسندگان
چکیده
We propose a method for simultaneously translating from a single source language to multiple target languages T1, T2, etc. The motivation behind this method is that if we only have a weak language model for T1 and translations in T1 and T2 are associated, we can use the information from a strong language model over T2 to disambiguate the translations in T1, providing better translation results. As a specific framework to realize multi-target translation, we expand the formalism of synchronous context-free grammars to handle multiple targets, and describe methods for rule extraction, scoring, pruning, and search with these models. Experiments find that multi-target translation with a strong language model in a similar second target language can provide gains of up to 0.8-1.5 BLEU points.1
منابع مشابه
Efficient Multi-Pass Decoding for Synchronous Context Free Grammars
We take a multi-pass approach to machine translation decoding when using synchronous context-free grammars as the translation model and n-gram language models: the first pass uses a bigram language model, and the resulting parse forest is used in the second pass to guide search with a trigram language model. The trigram pass closes most of the performance gap between a bigram decoder and a much...
متن کاملEfficient Multi-pass Decoding for Synchronous Context Free Grammars
We take a multi-pass approach to machine translation decoding when using synchronous context-free grammars as the translation model and n-gram language models: the first pass uses a bigram language model, and the resulting parse forest is used in the second pass to guide search with a trigram language model. The trigram pass closes most of the performance gap between a bigram decoder and a much...
متن کاملA Statistical Machine Translation Model Based on a Synthetic Synchronous Grammar
Recently, various synchronous grammars are proposed for syntax-based machine translation, e.g. synchronous context-free grammar and synchronous tree (sequence) substitution grammar, either purely formal or linguistically motivated. Aiming at combining the strengths of different grammars, we describes a synthetic synchronous grammar (SSG), which tentatively in this paper, integrates a synchronou...
متن کاملLearning Synchronous Grammars for Semantic Parsing with Lambda Calculus
This paper presents the first empirical results to our knowledge on learning synchronous grammars that generate logical forms. Using statistical machine translation techniques, a semantic parser based on a synchronous context-free grammar augmented with λoperators is learned given a set of training sentences and their correct logical forms. The resulting parser is shown to be the bestperforming...
متن کاملRule extraction for multi bottom-up tree transducers
Following the invention of computers, it was always a dream to obtain translations automatically. If we give a machine a sentence it should return a sentence in another language expressing the same meaning. In the subfield of statistical machine translation (SMT), this translation is achieved with the help of statistical models. Those models use large text collections to automatically learn bas...
متن کامل