On the Impact of Various Types of Noise on Neural Machine Translation
Table 1: Adding noisy web crawled data (raw data from paracrawl.eu) to a WMT 2017 German–English statistical system obtains small gains (+1.2 BLEU), a neural system falls apart (–9.9 BLEU).
['[EMPTY]', '[BOLD] NMT', '[BOLD] SMT']
In this work, we consider another challenge to neural machine translation: noisy parallel data. Here, we add an equally sized noisy web crawled corpus to high quality training data provided by the shared task of the Conference on Machine Translation (WMT). This addition leads to a 1.2 BLEU point increase for the statistical machine translation system, but degrades the neural machine translation system by 9.9 BLEU.