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Neural Machine Translation Decoding with Terminology Constraints
Despite the impressive quality improvements yielded by neural machine translation (NMT) systems, controlling their translation output to adhere to user-provided terminology constraints remains an open problem.
Accelerating NMT Batched Beam Decoding with LMBR Posteriors for Deployment
We describe a batched beam decoding algorithm for NMT with LMBR n-gram posteriors, showing that LMBR techniques still yield gains on top of the best recently reported results with Transformers.
Why not be Versatile? Applications of the SGNMT Decoder for Machine Translation
SGNMT is a decoding platform for machine translation which allows paring various modern neural models of translation with different kinds of constraints and symbolic models.
Speed-Constrained Tuning for Statistical Machine Translation Using Bayesian Optimization
We address the problem of automatically finding the parameters of a statistical machine translation system that maximize BLEU scores while ensuring that decoding speed exceeds a minimum value.
