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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 Replacing Linguists with Dummies: A Serious Need for Trivial Baselines in Multi-Task Neural Machine Translation Kondratyuk Daniel; Cardenas Ronald; Bojar Ondřej In: Prague Bulletin of Mathematical Linguistics , Vol 113, Iss 1, Pp 31-40 (2019) (2019) BASE Show details 2 Training Tips for the Transformer Model Popel Martin; Bojar Ondřej In: Prague Bulletin of Mathematical Linguistics , Vol 110, Iss 1, Pp 43-70 (2018) (2018) BASE Show details 3 Visualizing Neural Machine Translation Attention and Confidence Rikters Matīss; Fishel Mark; Bojar Ondřej In: Prague Bulletin of Mathematical Linguistics , Vol 109, Iss 1, Pp 39-50 (2017) (2017) BASE Show details 4 Extracting Parallel Paragraphs from Common Crawl Kúdela Jakub; Holubová Irena; Bojar Ondřej In: Prague Bulletin of Mathematical Linguistics , Vol 107, Iss 1, Pp 39-56 (2017) (2017) BASE Show details 5 Evaluating Machine Translation Quality Using Short Segments Annotations Macháček Matouš; Bojar Ondřej In: Prague Bulletin of Mathematical Linguistics , Vol 103, Iss 1, Pp 85-110 (2015) (2015) Abstract: We propose a manual evaluation method for machine translation (MT), in which annotators rank only translations of short segments instead of whole sentences. This results in an easier and more efficient annotation. We have conducted an annotation experiment and evaluated a set of MT systems using this method. The obtained results are very close to the official WMT14 evaluation results. We also use the collected database of annotations to automatically evaluate new, unseen systems and to tune parameters of a statistical machine translation system. The evaluation of unseen systems, however, does not work and we analyze the reasons Keyword: Computational linguistics. Natural language processing; P98-98.5 URL: https://doaj.org/article/8410fb61b1664506801d3ee4badd35df https://doi.org/10.1515/pralin-2015-0005 BASE Hide details 6 Resources for Indonesian Sentiment Analysis Franky; Bojar Ondřej; Veselovská Kateřina In: Prague Bulletin of Mathematical Linguistics , Vol 103, Iss 1, Pp 21-41 (2015) (2015) BASE Show details 7 TmTriangulate: A Tool for Phrase Table Triangulation Hoang Duc Tam; Bojar Ondřej In: Prague Bulletin of Mathematical Linguistics , Vol 104, Iss 1, Pp 75-86 (2015) (2015) BASE Show details

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