Langsmith: An Interactive Academic Text Revision System (2020)

Abstract: Despite the current diversity and inclusion initiatives in the academic community, researchers with a non-native command of English still face significant obstacles when writing papers in English. This paper presents the Langsmith editor, which assists inexperienced, non-native researchers to write English papers, especially in the natural language processing (NLP) field. Our system can suggest fluent, academic-style sentences to writers based on their rough, incomplete phrases or sentences. The system also encourages interaction between human writers and the computerized revision system. The experimental results demonstrated that Langsmith helps non-native English-speaker students write papers in English. The system is available at https://emnlp-demo.editor.langsmith.co.jp/ .

## introduction currently, diversity and inclusion in the natural language processing (nlp) community are encouraged. in fact, at the latest nlp conference at the time of writing 1 , papers were submitted from more than 50 countries. however, one obstacle can limit this diversity: the papers must be written in english. writing papers in english can be a daunting task, especially for inexperienced, non-native speakers. these writers often struggle to put their ideas into words. to address this problem, we built the langsmith editor, an assistance system for writing nlp papers in english. @xcite the main feature in langsmith is a revision function, which suggests fluent, academic-we observed significant differences in the results between a and b. we saw difference in the results between a and b. based on such difficulties, our system provides two ways for users to customize the revision: the users can (i) request specific revisions, and (ii) select a suitable revision from diverse candidates (figure 1 ). in particular, the request stage allows users to specify the parts that require intensive revision. our experiments demonstrate the effectiveness of our system. specifically, students whose first language is japanese, which differs greatly from english, managed to write better drafts when working with langsmith. langsmith has other assistance features as well, such as text completion with a neural language model. furthermore, the communication between the server and the web frontend is achieved via a protocol specialized in writing software called the text editing assistance smartness protocol for natural language (teaspn) (hagiwara et al., 2019). we hope that our system will help the nlp community and researchers, especially those lacking a native command of english. foot_0 2 related work 2.1 natural language processing for academic writing academic writing assistance has gained considerable attention in nlp (wu et al., 2010; yimam et al., 2020; lee and webster, 2012), and several shared tasks have been organized (dale and kilgarriff, 2011; daudaravičius, 2015). these tasks focus on polishing texts in already published articles or documents near completion. in contrast, this study focuses on revising texts in the earlier stages of writing (e.g., first drafts), where inexperienced, non-native authors might even struggle to convey their ideas accurately. ito et al. (2019) introduced a dataset and models for revising early-stage drafts, and the 1-to-n nature of the revisions was pointed out. we tackled this difficulty by designing an overall demonstration system, including a user interface. ## experiments and results we demonstrate the effectiveness of humanmachine interactions in revising drafts implemented in our system. we also check whether the request stage in the revision feature works adequately. ## conclusions we have presented langsmith, an academic writing assistance system. langsmith provides a writing environment, in which human writers use several assistance features to improve the quality of texts. our experiments suggest that our system is useful for inexperienced, non-native writers in revising english-language papers. we are aware that our experimental settings were not fully well-designed (e.g., we had only japanese participants, and no human evaluation). we will evaluate langsmith in more sophisticated settings. we hope that our system contributes to breaking language barriers in the academic community.