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Crowd-sourcing NLG Data: Pictures Elicit Better Data.
Jekaterina Novikova
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Oliver Lemon
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Verena Rieser
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Paper Details:
Month: September 5-8
Year: 2016
Location: Edinburgh, UK
Venue:
INLG |
WS |
SIG: SIGGEN
Citations
URL
Towards an Automatic Assessment of Crowdsourced Data for NLU
Patricia Braunger
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Wolfgang Maier
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Jan Wessling
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Maria Schmidt
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A Deep Ensemble Model with Slot Alignment for Sequence-to-Sequence Natural Language Generation
Juraj Juraska
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Panagiotis Karagiannis
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Kevin Bowden
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Marilyn Walker
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The aNALoGuE Challenge: Non Aligned Language GEneration
Jekaterina Novikova
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Verena Rieser
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Analysing Data-To-Text Generation Benchmarks
Laura Perez-Beltrachini
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Claire Gardent
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Harvesting Creative Templates for Generating Stylistically Varied Restaurant Reviews
Shereen Oraby
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Sheideh Homayon
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Marilyn Walker
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How Would You Say It? Eliciting Lexically Diverse Dialogue for Supervised Semantic Parsing
Abhilasha Ravichander
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Thomas Manzini
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Matthias Grabmair
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Graham Neubig
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Jonathan Francis
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Eric Nyberg
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Controlling Personality-Based Stylistic Variation with Neural Natural Language Generators
Shereen Oraby
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Lena Reed
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Shubhangi Tandon
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Sharath T.S.
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Stephanie Lukin
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Marilyn Walker
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Characterizing Variation in Crowd-Sourced Data for Training Neural Language Generators to Produce Stylistically Varied Outputs
Juraj Juraska
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Marilyn Walker
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E2E NLG Challenge Submission: Towards Controllable Generation of Diverse Natural Language
Henry Elder
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Sebastian Gehrmann
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Alexander O’Connor
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Qun Liu
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http://swoogle.umbc.edu/SimService/api.html
Field Of Study
Task
Semantic Similarity
Language Generation
Language
English
Japanese
Dataset
Spoken Dialog
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