Paper Info
Title
Visual Saliency and Crowdsourcing-based Priors for an In-car Situated Dialog System.
Abstract
This paper addresses issues in situated language understanding in a moving car. We propose a reference resolution method to identify user queries about specific target objects in their surroundings. We investigate methods of predicting which target object is likely to be queried given a visual scene and what kind of linguistic cues users naturally provide to describe a given target object in a situated environment. We propose methods to incorporate the visual saliency of the visual scene as a prior. Crowdsourced statistics of how people describe an object are also used as a prior. We have collected situated utterances from drivers using our research system, which was embedded in a real vehicle. We demonstrate that the proposed algorithms improve target identification rate by 15.1%.
Year
DOI
Venue
2015
10.1145/2818346.2820748
ICMI
Keywords
Field
DocType
Situated dialog, In-car interaction, Visual saliency, Crowdsourcing, Multimodal interaction
Situated,Computer vision,Multimodal interaction,Computer science,Crowdsourcing,Human–computer interaction,Artificial intelligence,Dialog system,Prior probability,Language understanding,Visual saliency
Conference
Citations 
PageRank 
References 
2
0.38
18
Authors
1
Name
Order
Citations
PageRank
Teruhisa Misu1195.89