MultiMediate '22：组交互中的反向信道检测和一致性估计
MultiMediate '22: Backchannel Detection and Agreement Estimation in Group Interactions
摘要：
后通道，即听者的短感叹词，具有重要的元会话目的，如表示注意或表示同意。尽管他们的关键作用，自动分析的backchannels在群体互动已在很大程度上被忽视了。MultiMediate挑战首次解决了组对话中反向通道的反向通道检测和协议估计任务。本文介绍了MultiMediate挑战，并提出了一套新的注释组成的7234反向通道实例的MPIIGroupInteraction数据集。每个反向通道都附加了它对当前说话者表示同意的程度。除了对收集的注释进行分析外，我们还为这两个挑战任务提供了基线结果。
英文摘要：
Backchannels, i.e. short interjections of the listener, serve important meta-conversational purposes like signifying attention or indicating agreement. Despite their key role, automatic analysis of backchannels in group interactions has been largely neglected so far. The MultiMediate challenge addresses, for the first time, the tasks of backchannel detection and agreement estimation from backchannels in group conversations. This paper describes the MultiMediate challenge and presents a novel set of annotations consisting of 7234 backchannel instances for the MPIIGroupInteraction dataset. Each backchannel was additionally annotated with the extent by which it expresses agreement towards the current speaker. In addition to a an analysis of the collected annotations, we present baseline results for both challenge tasks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
