Definition: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Input: Recent works on end-to-end neural network-based architectures for machine translation have shown promising results for English-French and English-German translation. Unlike these language pairs, however, in the majority of scenarios, there is a lack of high quality parallel corpora. In this work, we focus on applying neural machine translation to challenging/low-resource languages Turkish and low-resource domains such as parallel corpora of Chinese chat messages. In particular, we investigated how to leverage abundant monolingual data for these low-resource translation tasks. Without the use of external alignment tools, we obtained up to a 1.96 BLEU score improvement with our proposed method compared to the previous best result in Turkish-to-English translation on the IWLST 2014 dataset. On Chinese-toEnglish translation by using the OpenMT 2015 dataset, we were able to obtain up to a 1.59 BLEU score improvement over phrase-based and hierarchical phrase-based baselines.

On Using Monolingual Corpora in Neural Machine Translation