Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting out of Shaanxi, People’s Republic of C hina, by NewsRx editors, research stated, “This article aimed to address the pro blems of word order confusion, context dependency, and ambiguity in traditional machine translation (MT) methods for verb recognition.” Our news journalists obtained a quote from the research from Xi’an Jiaotong Univ ersity: “By applying advanced intelligent algorithms of artificial intelligence, verb recognition can be better processed and the quality and accuracy of MT can be improved. Based on Neural machine translation (NMT), basic attention mechani sms, historical attention information, dynamically obtain information related to the generated words, and constraint mechanisms were introduced to embed semanti c information, represent polysemy, and annotate semantic roles of verbs. This ar ticle used the Workshop on machine translation (WMT), British National Corpus (B NC), Gutenberg, Reuters Corpus, OpenSubtitles corpus, and enhanced the data in t he corpus. The improved NMT model was compared with traditional NMT models, Rule Based machine translation (RBMT), and Statistical machine translation (SMT).”
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