Abstract

The article examines certain periods of machine translation development and the methods used to create various machine translation systems. To ensure correct historical periodization, the author defines the criteria for classifying the development of machine translation. Special attention is paid to the development of individual machine translation systems, as well as the events that had a significant impact on both the development and the hindrance of progress in the field of machine translation. Additionally, the author considers the ALPAC report and its subsequent “quiet period” of machine translation development, analyses the key specialists who have been involved in the development and improvement of machine translation systems and machine translation technologies, categorizing them into four large groups. The article reviews the dominant basis of machine translation research until the late 1980s, rooted in various linguistic rules such as parsing rules, lexical rules, lexical transfer rules, syntactic generation rules, morphology rules, etc.The author traces the emergence of the corpus-based method in machine translation, as well as its further expansion through experiments in computational modelling of cognition and perception, including the study of parallel computing, neural networks and connectionism, which offered the prospect of making the systems “learn” from past successes and failures. Besides, the author also examines the emergence of the interlingualapproach for multilingual translation of technical manuals and the history of the “pivot language”, along with the use of SLLP (specialized languages for linguistic programming).

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