Facilitating the Communication of Politeness through Fine-Grained Paraphrasing

November 30, 2020 · Entered Twilight · 🏛 Conference on Empirical Methods in Natural Language Processing

"Last commit was 5.0 years ago (≥5 year threshold)"

Evidence collected by the PWNC Scanner

Repo contents: Evaluation.ipynb, Evaluation_Data.ipynb, How_to_Make_Strategy_Edits.ipynb, README.md, Training_Generation_Model.ipynb, bleu.py, data, generation_utils.py, openai_gpt_drg_strategized.py, output, perception_utils.py, plan_with_baselines.py, plan_with_ilp.py, pytorch_pretrained_bert, settings.py, strategy_manipulation.py

Authors Liye Fu, Susan R. Fussell, Cristian Danescu-Niculescu-Mizil arXiv ID 2012.00012 Category cs.CL: Computation & Language Cross-listed cs.AI, cs.CY, cs.HC Citations 18 Venue Conference on Empirical Methods in Natural Language Processing Repository https://github.com/CornellNLP/politeness-paraphrase ⭐ 9 Last Checked 1 month ago

Abstract

Aided by technology, people are increasingly able to communicate across geographical, cultural, and language barriers. This ability also results in new challenges, as interlocutors need to adapt their communication approaches to increasingly diverse circumstances. In this work, we take the first steps towards automatically assisting people in adjusting their language to a specific communication circumstance. As a case study, we focus on facilitating the accurate transmission of pragmatic intentions and introduce a methodology for suggesting paraphrases that achieve the intended level of politeness under a given communication circumstance. We demonstrate the feasibility of this approach by evaluating our method in two realistic communication scenarios and show that it can reduce the potential for misalignment between the speaker's intentions and the listener's perceptions in both cases.