A Multifaceted Study On Eye Contact Based Speaker Identification In Three-Party Conversations

To precisely understand human gaze behaviors in three-party conversations, this work is dedicated to look into whether the speaker can be reliably identified from the interlocutors in a three-party conversation on the basis of the interactive behaviors of eye contact, where speech signals are not provided. Derived from a pre-recorded, multimodal, and three-party conversational behavior dataset, a statistical framework is proposed to determine who is the speaker from the interactive behaviors of eye contact. Additionally, with the aid of virtual human technologies, a user study is conducted to study whether subjects are capable of distinguishing the speaker from the listeners according to the gaze behaviors of the interlocutors alone. Our results show that eye contact provides a reliable cue for the identification of the speaker in three-party conversations.