How Much Information Does a Human Translator Add to the Original?

作者: Barret Zoph, Marjan Ghazvininejad, Kevin Knight

摘要

We ask how much information a human translator adds to an original text, and we provide a bound. We address this question in the context of bilingual text compression: given a source text, how many bits of additional information are required to specify the target text produced by a human translator? We develop new compression algorithms and establish a benchmark task.

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