On the Impact of Various Types of Noise on Neural Machine Translation

Huda Khayrallah; Philipp Koehn

On the Impact of Various Types of Noise on Neural Machine Translation

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arxiv 1805.12282 v1 pith:2DAMWJ2X submitted 2018-05-31 cs.CL

Huda Khayrallah , Philipp Koehn This is my paper · ORCID

classification cs.CL

keywords noiseneuralmachinetranslationtypesimpactmodelsstatistical

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We examine how various types of noise in the parallel training data impact the quality of neural machine translation systems. We create five types of artificial noise and analyze how they degrade performance in neural and statistical machine translation. We find that neural models are generally more harmed by noise than statistical models. For one especially egregious type of noise they learn to just copy the input sentence.

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