首页|Studies from Hamad Bin Khalifa University Reveal New Findings on Machine Transla tion (Cross-linguistic authorship attribution and gender profiling. Machine tran slation as a method for bridging the language gap)
Studies from Hamad Bin Khalifa University Reveal New Findings on Machine Transla tion (Cross-linguistic authorship attribution and gender profiling. Machine tran slation as a method for bridging the language gap)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on machine translation h ave been presented. According to news reporting from Doha, Qatar, by NewsRx jour nalists, research stated, "This study explores the feasibility of cross-linguist ic authorship attribution and the author's gender identification using Machine T ranslation (MT)." Our news journalists obtained a quote from the research from Hamad Bin Khalifa U niversity: "Computational stylistics experiments were conducted on a Greek blog corpus translated into English using Google's Neural MT. A Random Forest algorit hm was employed for authorship and gender profiling, using different feature gro ups [Author's Multilevel N-gram Profiles, quantitative lingui stics (QL), and cross-lingual word embeddings (CLWE)] in both original and translated texts."
Hamad Bin Khalifa UniversityDohaQata rAsiaEmerging TechnologiesMachine LearningMachine Translation
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