论文标题
多媒体'22：小组相互作用中的后班检测和一致性估计
MultiMediate '22: Backchannel Detection and Agreement Estimation in Group Interactions
论文作者
论文摘要
回音渠道，即听众的简短插入，具有重要的元转换目的，例如表示注意力或指示一致。尽管它们的关键作用，但到目前为止，对群体互动中的后拨渠的自动分析已被大大忽视。多层挑战的地址首次在小组对话中首次从回渠道进行了回渠道检测和协议估算的任务。本文介绍了多层挑战，并提出了一组新的注释，该注释由MPIigrOupContraction数据集的7234个回流实例组成。另外，每个后拨渠都以对当前发言人表示同意的程度。除了对收集注释的分析外，我们还为这两个挑战任务提供了基线结果。
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.
