Facilitating the Communication of Politeness through Fine-Grained Paraphrasing (2020)

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.

## introduction technological developments have greatly enhanced our communication experience, providing the opportunity to overcome geographic, cultural and language barriers to interact with people from different backgrounds in diverse settings @xcite . however, this opportunity brings additional challenges for the interlocutors, as they need to adjust their language to increasingly diverse communication circumstances. as humans, we often make conscious attempts to account for the communication setting. for instance, we may simplify our expressions if we know our listener has relatively limited language proficiency, and we tend to be more polite towards people with higher status. however, managing these stylistic adjustments can be cognitively taxing, especially when we are missing relevant information-e.g., the language proficiency or the status of a conversational partner we meet online. if we do not adjust our language, we risk not properly conveying our pragmatic intentions @xcite . in particular, berlo's sender-message-channel-receiver model @xcite points to two potential circumstance-specific causes for misalignments between intentions and perceptions (figure 1 ). in this work we explore a method for assisting speakers to avoid such misalignments by suggesting for each message a paraphrase that is more likely to convey the original pragmatic intention when communicated in a given circumstance, as determined by the properties of the sender, channel, and receiver. as a case study, in this work, we focus on one particular pragmatic aspect: politeness. it is important to assist people to accurately transmit their intended politeness, as this interpersonal style @xcite plays a key role in social interactions @xcite @xcite . furthermore, politeness is known to be a circumstance-sensitive phenomenon @xcite @xcite , making it a good case for our study. concretely, we propose the task of generating a paraphrase for a given message that is more likely to deliver the intended level of politeness after transmission (henceforth intention-preserving), considering the properties of the sender, channel, and receiver (section 3). taking the properties of the channel into account is important because communication channels may not always faithfully deliver messages (figure 1a ). for example, in translated communication, politeness signals can often be lost or corrupted @xcite . to demonstrate the potential of our framework in mitigating channel-induced misunderstandings, we apply it to suggest paraphrases that are safer to transmiti.e., less likely to have their politeness alteredover a commercial machine translation service. we also need to account for the fact that the sender and receiver can have different interpretations of the same message (figure 1b ). for example, people may perceive politeness cues differently depending on their cultural background @xcite . in our second application scenario, the interlocutors' perceptions of politeness are misaligned, and we aim to suggest paraphrases that reduce the potential for misinterpretation. to successfully produce such circumstancesensitive paraphrases, we need to depart from existing style transfer methodology (see @xcite for a survey, and @xcite for politeness transfer in particular). first, since we must account for arbitrary levels of misalignment, we need fine-grained control over the target stylistic level, as opposed to binary switches (e.g., from impolite to polite). second, we need to determine the target stylistic level at run time, in an ad hoc fashion, rather than assuming predefined targets. to overcome these new technical challenges, we start from the intuition that the same level of politeness can be conveyed through different combinations of pragmatic strategies @xcite , with some being more appropriate to the given circumstance than others. we consider a classic two-step approach (section 4), separating planning-choosing a viable combination of strategies that can achieve a desired stylistic level in a particular circumstance-, from the step of realization-incorporating this plan into generation outputs. for a given fine-grained target stylistic level (i.e., the level intended by the sender), we find the optimal strategy plan via integer linear programming (ilp). we then realize this plan using a modification of the 'delete-retrieve-generate' (drg) paradigm @xcite that allows for strategy-level control in generation. our experimental results indicate that in both our application scenarios, our method can suggest paraphrases that narrow the potential gap between the intended and perceived politeness, and thus better preserve the sender's intentions. these results show that automated systems have the potential to help people better convey their intentions in new communication circumstances, and encourage further work exploring the feasibility and implications of such communication assistance applications. to summarize, in this work, we motivate and formulate the task of circumstance-sensitive intentionpreserving paraphrasing (section 3). focusing on the case of pragmatic intentions, we introduce a model for paraphrasing with fine-grained politeness control (section 4). we evaluate our method in two realistic communication scenarios to demonstrate the feasibility of the approach (section 5). ## further related work style transfer. there has been a wide range of efforts in using nlp techniques to generate alternative expressions, leading to tasks such as text simplification (see @xcite for a survey), or more generally, paraphrase generation @xcite @xcite . when such paraphrasing effort is focused on the stylistic aspect, it is also referred to as text style transfer, which has attracted a lot of attention in recent years @xcite @xcite . while these tasks are focused on satisfying specific predefined linguistic properties at the utterance-level, they are not designed for fine-grained adjustments to changing non-textual communication circumstances. controllable generation. style transfer or paraphrasing can both be seen as a special case of the broader task of controllable text generation @xcite @xcite . while not focused on paraphrasing, relevant work in this area aims at controling the level of politeness for translation @xcite or dialog response @xcite . ai-assisted communications or writing. beyond paraphrasing, ai tools have been used to provide communication or writing assistance in diverse settings: from the mundane task of grammar and spell checking @xcite , to creative writing @xcite , to negotiations @xcite , and has led to discussions of ethical implications @xcite . ## task formulation given a message that a sender attempts to communicate to a receiver over a particular communication channel, the task of circumstance-sensitive intention-preserving paraphrasing is to generate a paraphrase that is more likely to convey the intention of the sender to the receiver after transmission, under the given communication circumstance. formulation. to make this task more tractable, our formulation considers a single gradable stylistic aspect of the message that can be realized through a collection of pragmatic strategies (denoted as s). while in this work we focus on politeness, other gradable stylistic aspects might include formality, humor and certainty. we can then formalize the relevant features of the communication circumstance as follows: with our focus on politeness, our task can then be more precisely stated as follows: given an input message m, we aim to generate a politeness paraphrase for m, under the circumstance specified by (f send , f c , f rec ), such that the level of politeness perceived by the receiver is as close to that intended by the sender as possible. we show that our theoretically-grounded formulation can model naturally-occurring challenges in communication, by considering two possible application scenarios, each corresponding to a source of misalignment highlighted in figure 1 . application a: translated communication. we first consider the case of conversations mediated by translation services, where channel-induced misunderstandings can occur (figure 1a ): mt models may systematically drop certain politeness cues due to technical limitations or mismatches between the source and target languages. for instance, despite the difference in intended politeness level (indicated in parentheses) of the following two versions of the same request, 1 could you please proofread this article? (polite) can you proofread this article? (somewhat polite) microsoft bing translator would translate both versions to the same utterance in chinese. foot_1 by dropping the politeness marker 'please', and not making any distinction between 'could you' and 'can you', the message presented to the chinese receiver is likely to be more imposing than originally desired by the english sender. to avoid such channel-induced misunderstandings, the sender may consider using only strategies that are known to be safe with the specific mt system they use. 3 however, since the inner mechanics of such systems are often opaque (and in constant flux), the sender would benefit from automatic guidance in constructing such paraphrases. ## method when compared to style transfer tasks, our circumstance-sensitive intention-preserving paraphrasing task gives rise to important new technical challenges. first, in order to minimize the gap in perceptions, we need to have fine-grained control over the stylistic aspect, as opposed to switching between two pre-defined binarized targets (e.g., polite vs. impolite). second, the desired degree of change is only determined at run-time, depending on the speaker's intention and on the communication circumstance. we address these challenges by developing a method that allows for ad hoc and fine-grained paraphrase planning and realization. our solution starts from a strategy-centered view: instead of aiming for monolithic style labels, we think of pragmatic strategies as (stylistic) lego bricks. these can be stacked together in various combinations to achieve similar stylistic levels. depending on the circumstance, some bricks might, or might not, be available. therefore, given a message with an intended stylistic level, our goal is to find the optimal collection of available bricks that can convey the same level-ad hoc fine-grained planning. given this optimal collection, we need to assemble it with the rest of the message into a valid paraphrase-fine-grained realization. politeness strategies. in the case of politeness, we derive the set of pragmatic strategies from prior work @xcite @xcite . we focus on strategies that are realized through local linguistic markers. for instance, the subjunctive strategy can be realized through the use of markers like could you or would you. in line with prior work, we further assume that markers realizing the same strategy has comparable strength in exhibiting politeness and are subject to the same constraints. the full list of 18 strategies we consider (along with their example usages) can be found in ## evaluation to test the feasibility of our approach, we set up two parallel experiments with different circumstance specifications, so that each illustrates one potential source of misalignment as described in section 3. 11 ## discussion in this work, we motivate and formulate the task of circumstance-sensitive intention-preserving paraphrasing and develop a methodology that shows promise in helping people more accurately communicate politeness under different communication settings. the results and limitations of our method open up several natural directions for future work. modeling politeness perceptions. we use a simple linear regression model to approximate how people internally interpret politeness and restrict our attention to only the set of local politeness strategies. future work may consider more comprehensive modeling of how people form politeness perceptions or obtain more reliable causal estimates for strategy strength @xcite . task formulation. we make several simplifying assumptions in our task formulation. first, we focus exclusively on a gradable stylistic aspect that is mostly decoupled from the content @xcite , reducing the complexity required from both the perception and the generation models. future work may consider more complex stylistic aspects and strategies that are more tied to the content, such as switching from active to passive voice. second, we consider binary channel constraints, but in reality, the channel behavior is often less clear-cut. future work can aim to propose more general formulations that encapsulate more properties of the circumstance. forms of assistance. while we have focused on offering paraphrasing options as the form of assistance, it is not the only type of assistance possible. as our generation model may not (yet) match the quality of human rewrites, there can be a potential trade-off. while an entirely automatic assistance option may put the least cognitive load on the user, it may not produce the most natural and effective rewrite, which may be possible if humans are more involved. hence, while we work towards providing fully automated suggestions, we might also want to utilize the language ability humans possess and consider assistance approaches in the form of interpretable (partial) suggestions. evaluation. in our experiments, we have relied exclusively on model predictions to estimate the level of misalignment in politeness perceptions. given the fine-grained and individualized nature of the task, using humans to ascertain the politeness of the outputs would require an extensive and relatively complex annotation setup (e.g., collecting finegrained labels from annotators with known backgrounds for training and evaluating individualized perception models). furthermore, to move towards more practical applications, we would also need to conduct communication-based evaluation (newman et al., 2020) in addition to annotating individual utterances. future work can consider adapting experiment designs from prior work @xcite to establish the impact of offering such intention-preserving paraphrases in real conversations, potentially by considering downstream outcomes.