Issue #30 – Reducing loss of meaning in Neural MT
28 Mar19 Issue #30 – Reducing loss of meaning in Neural MT Author: Raj Patel, Machine Translation Scientist @ Iconic An important, and perhaps obvious feature of high-quality machine translation systems is that they preserve the meaning of the source in the translation. That is to say, if we have two different source sentences with slightly different meanings, we should have slightly different translations. However, this nuance can be a challenge, even for state-of-the-art systems, particularly in cases where source […]
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