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Optimising Information Presentation for Spoken Dialogue Systems
Verena Rieser
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Oliver Lemon
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Xingkun Liu
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Paper Details:
Month: July
Year: 2010
Location: Uppsala, Sweden
Venue:
ACL |
Citations
URL
Optimising Incremental Dialogue Decisions Using Information Density for Interactive Systems
Nina Dethlefs
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Helen Hastie
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Verena Rieser
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Oliver Lemon
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Finding middle ground? Multi-objective Natural Language Generation from time-series data
Dimitra Gkatzia
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Helen Hastie
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Oliver Lemon
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Learning and Evaluation of Dialogue Strategies for New Applications: Empirical Methods for Optimization from Small Data Sets
Verena Rieser
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Oliver Lemon
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Hierarchical Reinforcement Learning and Hidden Markov Models for Task-Oriented Natural Language Generation
Nina Dethlefs
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Heriberto Cuayáhuitl
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Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data
Dimitra Gkatzia
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Helen Hastie
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Oliver Lemon
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Sequence-to-Sequence Generation for Spoken Dialogue via Deep Syntax Trees and Strings
Ondřej Dušek
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Filip Jurčíček
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Generation Under Uncertainty
Oliver Lemon
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Srini Janarthanam
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Verena Rieser
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Optimising Natural Language Generation Decision Making For Situated Dialogue
Nina Dethlefs
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Heriberto Cuayáhuitl
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Jette Viethen
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“The day after the day after tomorrow?” A machine learning approach to adaptive temporal expression generation: training and evaluation with real users
Srinivasan Janarthanam
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Helen Hastie
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Oliver Lemon
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Xingkun Liu
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Optimising Incremental Generation for Spoken Dialogue Systems: Reducing the Need for Fillers
Nina Dethlefs
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Helen Hastie
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Verena Rieser
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Oliver Lemon
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Generating Student Feedback from Time-Series Data Using Reinforcement Learning
Dimitra Gkatzia
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Helen Hastie
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Srinivasan Janarthanam
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Oliver Lemon
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Multi-adaptive Natural Language Generation using Principal Component Regression
Dimitra Gkatzia
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Helen Hastie
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Oliver Lemon
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Beyond On-hold Messages: Conversational Time-buying in Task-oriented Dialogue
Soledad López Gambino
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Sina Zarrieß
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David Schlangen
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https://www.classic-project.org/corpora/
Field Of Study
Language
English
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