Paper Info
Title
Easy Things First: Installments Improve Referring Expression Generation For Objects In Photographs
Abstract
Research on generating referring expressions has so far mostly focussed on "oneshot reference", where the aim is to generate a single, discriminating expression. In interactive settings, however, it is not uncommon for reference to be established in "installments", where referring information is offered piecewise until success has been confirmed. We show that this strategy can also be advantageous in technical systems that only have uncertain access to object attributes and categories. We train a recently introduced model of grounded word meaning on a data set of REs for objects in images and learn to predict semantically appropriate expressions. In a human evaluation, we observe that users are sensitive to inadequate object names - which unfortunately are not unlikely to be generated from low-level visual input. We propose a solution inspired from human task-oriented interaction and implement strategies for avoiding and repairing semantically inaccurate words. We enhance a word-based REG with context-aware, referential installments and find that they substantially improve the referential success of the system.
Year
Venue
DocType
2016
PROCEEDINGS OF THE 54TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 1
Conference
Volume
Citations 
PageRank 
P16-1
3
0.47
References 
Authors
20
2
Name
Order
Citations
PageRank
Sina Zarrieß1358.65
david schlangen2213.45