Real-Time Interruption Management System for Efficient Distributed Collaboration in Multi-tasking Environments

Abstract

Interruption dissemination in proactive systems remains a challenge for efficient human-machine collaboration, especially in real-time distributed collaborative environments. In this paper a real-time interruption management system (IMS) is proposed that leverages speech information, the most commonly used and available means of communication within collaborative distributed environments. The key aspect of this paper includes a proposed real-time IMS system that leverages lexical affirmation cues to infer the end of a task or task boundary as a candidate interruption time. The performance results show the proposed real-time lexical Affirmation Cues based Interruption Management System (ACE-IMS) outperforms the current baseline real-time IMS system within the existing literature. ACE-IMS has the potential of reducing disruptive interruptions without incurring excessive missed opportunities to disseminate interruptions by utilizing only the most frequently used mode of human communication: voice. Thereby, providing a promising new baseline to further the system development of real-time interruption management systems within the ever-growing distributed collaborative domain.