Active participation in a conversation is key to building common ground, since understanding is jointly tailored by producers and recipients. Overhearers are deprived of the privilege of performing grounding acts and can only conjecture about intended meanings. Still, data generation and annotation, modelling, training and evaluation of NLP dialogue models place reliance on the overhearing paradigm. How much of the underlying grounding processes are thereby forfeited? As we show, there is evidence pointing to the impossibility of properly modelling human meta-communicative acts with data-driven learning models. In this paper, we discuss this issue and provide a preliminary analysis on the variability of human decisions for requesting clarification. Most importantly, we wish to bring this topic back to the community's table, encouraging discussion on the consequences of having models designed to only "listen in".

翻译：积极参与对话是建立共同理解的关键，因为理解由说话者和接受者共同调整生成。旁听者被剥夺了进行共识行为的特权，只能推测潜在意图。然而，自然语言处理对话模型的数据生成与标注、建模、训练和评估却都依赖于旁听范式。由此，我们损失了多少潜在的共识过程？正如我们所展示的，有证据表明，完全依赖数据驱动的学习模型无法准确建模人类的元交际行为。本文讨论这一问题，并就人类请求澄清决策的变异性提供初步分析。最重要的是，我们希望将该议题重新带回学界讨论，鼓励探讨仅设计为“旁听”的模型所产生的后果。