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8 papers · 2 filters
Evaluation of Automatic Video Captioning Using Direct Assessment
Yvette Graham, George Awad, Alan Smeaton
We present Direct Assessment, a method for manually assessing the quality of automatically-generated captions for video. Evaluating the accuracy of video captions is particularly d…
Refining Source Representations with Relation Networks for Neural Machine Translation
Wen Zhang, Jiawei Hu, Yang Feng +1
Although neural machine translation (NMT) with the encoder-decoder framework has achieved great success in recent times, it still suffers from some drawbacks: RNNs tend to forget o…
Understanding State Preferences With Text As Data: Introducing the UN General Debate Corpus
Alexander Baturo, Niheer Dasandi, Slava J. Mikhaylov
Every year at the United Nations, member states deliver statements during the General Debate discussing major issues in world politics. These speeches provide invaluable informatio…
Deep Neural Machine Translation with Linear Associative Unit
Mingxuan Wang, Zhengdong Lu, Jie Zhou +1
Deep Neural Networks (DNNs) have provably enhanced the state-of-the-art Neural Machine Translation (NMT) with their capability in modeling complex functions and capturing complex l…
Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search
Chris Hokamp, Qun Liu
We present Grid Beam Search (GBS), an algorithm which extends beam search to allow the inclusion of pre-specified lexical constraints. The algorithm can be used with any model that…
Exploiting Cross-Sentence Context for Neural Machine Translation
Longyue Wang, Zhaopeng Tu, Andy Way +1
In translation, considering the document as a whole can help to resolve ambiguities and inconsistencies. In this paper, we propose a cross-sentence context-aware approach and inves…