Abstract
Inclusive writing is compulsory in formal communications. However, employees in private organizations, universities, and ministries often lack inclusive writing skills. For example, despite Italian grammar having masculine and feminine declensions of words, many official documents have a disrespectful prevalence of the masculine form. To promote inclusive writing practices, we present Inclusively, a language support tool that leverages natural language processing techniques to automatically identify instances of non-inclusive language and suggest more inclusive alternatives. The tool can be used as a text proofreader and, at the same time, fosters self-learning of inclusive writing forms. The recorded demo of the tool, available at https://youtu.be/3uiW_ti8wmY, shows how end-users can interact with Inclusively to feed new data, visualize the non-inclusive pieces of text, explore the list of alternative forms, and provide feedback or human annotations for system fine-tuning.
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Notes
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In compliance with the current privacy regulations.
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The code is available at https://github.com/MorenoLaQuatra/inclusively-demo.
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Acknowledgement
We thank Prof. Rachele Raus and Prof. Michela Tonti for their valuable work in defining the linguistic criteria for inclusivity and creating the corpus of Italian administrative documents.
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La Quatra, M., Greco, S., Cagliero, L., Cerquitelli, T. (2023). Inclusively: An AI-Based Assistant for Inclusive Writing. In: De Francisci Morales, G., Perlich, C., Ruchansky, N., Kourtellis, N., Baralis, E., Bonchi, F. (eds) Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track. ECML PKDD 2023. Lecture Notes in Computer Science(), vol 14175. Springer, Cham. https://doi.org/10.1007/978-3-031-43430-3_31
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