EMNLP 2015Main
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.