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A Statistical Model for Domain-Independent Text Segmentation
TLDR
A statistical method is proposed that finds the maximum-probability segmentation of a given text that does not require training data and can be applied to any text in any domain. Expand
ASPEC: Asian Scientific Paper Excerpt Corpus
TLDR
The details of the ASPEC (Asian Scientific Paper Excerpt Corpus), which is the first large-size parallel corpus of scientific paper domain, are described. Expand
Development of the Japanese WordNet
TLDR
The overview of the project to compile Japanese WordNet is described, which added Japanese equivalents to synsets of the Princeton WordNet and translated English sentences which are used in the SemCor annotation into Japanese and annotated them using the authors' Japanese Word net. Expand
A Comparison of Pivot Methods for Phrase-Based Statistical Machine Translation
TLDR
The phrase translation strategy significantly outperformed the sentence translation strategy and its relative performance was 0.92 to 0.97 compared to directly trained SMT systems. Expand
Overview of the Patent Translation Task at the NTCIR-7 Workshop
TLDR
This research is the first significant exploration into utilizing patent information for the evaluation of machine translations and performed the Patent Translation Task at the Seventh NTCIR Workshop. Expand
Sentence Embedding for Neural Machine Translation Domain Adaptation
TLDR
The NMT’s internal embedding of the source sentence is exploited and the sentence embedding similarity is used to select the sentences which are close to in-domain data to substantially improve NMT performance. Expand
Guiding Neural Machine Translation with Retrieved Translation Pieces
TLDR
This paper proposes a simple, fast, and effective method for recalling previously seen translation examples and incorporating them into the NMT decoding process, and compares favorably to another alternative retrieval-based method with respect to accuracy, speed, and simplicity of implementation. Expand
Neural Machine Translation with Supervised Attention
TLDR
Experiments on two Chinese-to-English translation tasks show that the supervised attention mechanism yields better alignments leading to substantial gains over the standard attention based NMT. Expand
Reliable Measures for Aligning Japanese-English News Articles and Sentences.
TLDR
The Daily Yomiuri reports on the history and present situation of the Chinese New Year celebrations in Beijing. Expand
Instance Weighting for Neural Machine Translation Domain Adaptation
TLDR
Two instance weighting technologies, i.e., sentence weighting and domain weighting with a dynamic weight learning strategy, are proposed for NMT domain adaptation and empirical results show that the proposed methods can substantially improve NMT performance. Expand
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