Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations 2020
DOI: 10.18653/v1/2020.acl-demos.37
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MMPE: A Multi-Modal Interface using Handwriting, Touch Reordering, and Speech Commands for Post-Editing Machine Translation

Abstract: The shift from traditional translation to postediting (PE) of machine-translated (MT) text can save time and reduce errors, but it also affects the design of translation interfaces, as the task changes from mainly generating text to correcting errors within otherwise helpful translation proposals. Since this paradigm shift offers potential for modalities other than mouse and keyboard, we present MMPE, the first prototype to combine traditional input modes with pen, touch, and speech modalities for PE of MT. Us… Show more

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Cited by 3 publications
(2 citation statements)
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“…We started our research on multi-modal CAT tools with an elicitation study (Herbig et al, 2019), which showed that pen, touch, and speech interaction, as well as combinations thereof, should be combined with mouse and keyboard to improve PE of MT. A prototype based on the proposed interactions allows users to "directly cross out or hand-write new text, drag and drop words for reordering, or use spoken commands to update the text in place" (Herbig et al, 2020b). Its evaluation with professional translators further showed that depending on the editing operation, different input modalities performed well (Herbig et al, 2020a).…”
Section: Multi-modal Approachesmentioning
confidence: 99%
“…We started our research on multi-modal CAT tools with an elicitation study (Herbig et al, 2019), which showed that pen, touch, and speech interaction, as well as combinations thereof, should be combined with mouse and keyboard to improve PE of MT. A prototype based on the proposed interactions allows users to "directly cross out or hand-write new text, drag and drop words for reordering, or use spoken commands to update the text in place" (Herbig et al, 2020b). Its evaluation with professional translators further showed that depending on the editing operation, different input modalities performed well (Herbig et al, 2020a).…”
Section: Multi-modal Approachesmentioning
confidence: 99%
“…We present the MMPE prototype (see Figure 1) which combines these modalities for PE of MT. A more detailed description of the prototype can be found in Herbig et al (2020), and a video demonstration is available at https://youtu.be/ H2YM2R8Wfd8.…”
Section: The Mmpe Prototypementioning
confidence: 99%