首页|Findings from University of Engineering & Management Update Knowle dge of Machine Translation (Consensus-based Machine Translation for Code-mixed T exts)
Findings from University of Engineering & Management Update Knowle dge of Machine Translation (Consensus-based Machine Translation for Code-mixed T exts)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Machine Translation are presented in a new report. According to news reporting from West Bengal, India, by NewsRx journalists, research stated, "Multilingualism in India is widespread due to its long history of foreign acquaintances. This leads to the presence of an audience familiar with conversing using more than one language."The news correspondents obtained a quote from the research from the University o f Engineering & Management, "Additionally, due to the social media boom, the usage of multiple languages to communicate has become extensive. Henc e, the need for a translation system that can serve the novice and monolingual u ser is the need of the hour. Such translation systems can be developed by method s such as statistical machine translation and neural machine translation, where each approach has its advantages as well as disadvantages. In addition, the para llel corpus needed to build a translation system, with code-mixed data, is not r eadily available. In the present work, we present two translation frameworks tha t can leverage the individual advantages of these pre-existing approaches by bui lding an ensemble model that takes a consensus of the final outputs of the prece ding approaches and generates the target output. The developed models were used for translating English-Bengali code-mixed data (written in Roman script) into t heir equivalent monolingual Bengali instances. A code-mixed to monolingual paral lel corpus was also developed to train the preceding systems."
West BengalIndiaAsiaEmerging Techn ologiesMachine LearningMachine TranslationUniversity of Engineering & Management
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NSTL
