Towards Decoding as Continuous Optimisation in Neural Machine Translation
We propose a novel decoding approach for neural machine translation (NMT) based on continuous optimisation. We reformulate decoding, a discrete optimization problem, into a continuous problem, such that optimization can make use of efficient gradient-based techniques. Our powerful decoding framework allows for more accurate decoding for standard neural machine translation models, as well as enabling decoding in intractable models such as intersection of several different NMT models. Our empirical results show that our decoding framework is effective, and can leads to substantial improvements in translations, especially in situations where greedy search and beam search are not feasible. Finally, we show how the technique is highly competitive with, and complementary to, reranking.
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationNMTRerankingTranslationSimilar Papers 제목 키워드 기반
Towards Decoding as Continuous Optimization in Neural Machine Translation
We propose a novel decoding approach for neural machine translation (NMT) based on continuous optimisation. We convert decoding - basically a discrete optimization problem - into a continuous optimization problem. The re…
Machine TranslationNMTRerankingTranslationRelay Decoding: Concatenating Large Language Models for Machine Translation
Leveraging large language models for machine translation has demonstrated promising results. However, it does require the large language models to possess the capability of handling both the source and target languages i…
Machine TranslationTranslationBayesian Optimisation for Machine Translation
This paper presents novel Bayesian optimisation algorithms for minimum error rate training of statistical machine translation systems. We explore two classes of algorithms for efficiently exploring the translation space,…
Bayesian OptimisationMachine TranslationTranslationTrainable Greedy Decoding for Neural Machine Translation
Recent research in neural machine translation has largely focused on two aspects; neural network architectures and end-to-end learning algorithms. The problem of decoding, however, has received relatively little attentio…
DecoderMachine TranslationTranslationEasy Guided Decoding in Providing Suggestions for Interactive Machine Translation
Machine translation technology has made great progress in recent years, but it cannot guarantee error free results. Human translators perform post editing on machine translations to correct errors in the scene of compute…
Machine TranslationNMTTranslation