A phenomenon-wise evaluation dataset for Japanese-English machine translation robustness. The dataset is based on the MTNT dataset, with additional annotations of four linguistic phenomena; Proper Noun, Abbreviated Noun, Colloquial Expression, and Varian
A phenomenon-wise evaluation dataset for Japanese-English machine translation robustness. The dataset is based on the MTNT dataset, with additional annotations of four linguistic phenomena; Proper Noun, Abbreviated Noun, Colloquial Expression, and Varian
The research articles considered in this study were limited to those published in last decade. Therefore, the period pertaining to our data set was from January 2014 until May 2023. This most recent period is representative for the last developments in this very specific topic. Moreover, until ...
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In terms of how the semi-transparent outline is created, the outline may be an image of an example telecommunication equipment component (that is correctly installed). Ideally, this image is representative of all telecommunication equipment components that are from the same model. For example, the...
for the spoken words of the proper name, wherein: each of the speech recognition candidates includes multiple components corresponding to the proper name, and each proper name component is a representative word for the proper name; checking, for each speech recognition candidate, the representative ...
(DAPI, blue) were visualized using confocal microscope. Photographs were taken in 5 randomly chosen fields (magn. 20×) per section in at least 4 tumors of each group. Representative photographs are shown. (b) Percentage of tumor area covered by blood vessels was calculated (mean ± SEM), ...
1987, (b) for breach of any condition as to title or quiet enjoyment implied by section 12 of the UK Sale of Goods Act 1979 or section 2 of the UK Supply of Goods and Services Act 1982; (c) for death or personal injury caused by our negligence or (d) for fraudulent ...
A phenomenon-wise evaluation dataset for Japanese-English machine translation robustness. The dataset is based on the MTNT dataset, with additional annotations of four linguistic phenomena; Proper Noun, Abbreviated Noun, Colloquial Expression, and Varian