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Interactive Machine Translation (IMT), is a specific sub-field of computer-aided translation. Under this translation paradigm, the computer software that assists the human translator attempts to predict the text the user is going to input by taking into account all the information it has available. Whenever such prediction is wrong and the user provides feedback to the system, a new prediction is performed considering the new information available. Such process is repeated until the translation provided matches the user's expectations. Interactive machine translation is specially interesting when translating texts in domains where it is not admissible to output a translation containing errors, hence requiring a human user to amend the translations provided by the system. In such cases, interactive machine translation has been proved to provide benefit to potential users.〔 〕〔 〕 Nevertheless, there is no commercial software that implements interactive machine translation yet and work done in the field is restrained to academic research. == History == Historically, interactive machine translation is born as an evolution of the computer-aided translation paradigm, where the human translator and the machine translation system were intended to work as a tandem.〔 〕 This first work was extended within the TransType research project, funded by the Canadian government. In this project, the human interaction was aimed towards producing the target text for the first time by embedding data-driven machine translation techniques within the interactive translation environment with the goal of achieving the best of both actors: the efficiency of the automatic system and the reliability of human translators. Later, a larger-scale research project, TransType2,〔 〔 funded by the European Commission extended such work by analyzing the incorporation of a complete machine translation system into the process, with the goal of producing a complete translation hypothesis, which the human user is allowed to amend or accept. If the user decides to amend the hypothesis, the system then attempts to make the best use of such feedback in order to produce a new translation hypothesis that takes into account the modifications introduced by the user. More recently, CASMACAT,〔 〕 also funded by the European Commission, aimed at developping novel types of assistance to human translators and integrated them into a new workbench, consisting of an editor, a server, and analysis and visualisation tools. The workbench was designed in a modular fashion and can be combined with existing computer aided translation tools. Furthermore, the CASMACAT workbench can learn from the interaction with the human translator by updating and adapting its models instantly based on the translation choices of the user.〔 〕〔 〕 Recent work on involving an extensive evaluation with human users〔 〕 revealed the fact that interactive machine translation may even be used by users that do not speak the source language in order to achieve near professional translation quality. Moreover, it also elucidated the fact that an interactive scenario is more beneficial than a classic post-edition scenario. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Interactive machine translation」の詳細全文を読む スポンサード リンク
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