Interruption detection in small-group dialogue remains accurate in simulated multi-group background noise when acoustic and textual features are combined, while an overlap-based heuristic collapses.
In: Das- gupta,S.,McAllester,D.(eds.)MakingaScienceofModelSearch:Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures
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The Impact of Background Speech on Interruption Detection in Collaborative Groups
Interruption detection in small-group dialogue remains accurate in simulated multi-group background noise when acoustic and textual features are combined, while an overlap-based heuristic collapses.