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Deep Neural Network Approach for the Dialog State Tracking Challenge
Matthew Henderson
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Blaise Thomson
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Steve Young
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Paper Details:
Month: August
Year: 2013
Location: Metz, France
Venue:
SIGDIAL |
WS |
SIG: SIGDIAL
Citations
URL
Deep Learning for Dialogue Systems
Yun-Nung Chen
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Asli Celikyilmaz
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Dilek Hakkani-Tür
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MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling
Paweł Budzianowski
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Tsung-Hsien Wen
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Bo-Hsiang Tseng
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Iñigo Casanueva
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Stefan Ultes
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Osman Ramadan
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Milica Gašić
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Open-Domain Neural Dialogue Systems
Yun-Nung Chen
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Jianfeng Gao
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Robust Coreference Resolution and Entity Linking on Dialogues: Character Identification on TV Show Transcripts
Henry Y. Chen
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Ethan Zhou
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Jinho D. Choi
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Multi-domain Dialog State Tracking using Recurrent Neural Networks
Nikola Mrkšić
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Diarmuid Ó Séaghdha
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Blaise Thomson
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Milica Gašić
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Pei-Hao Su
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David Vandyke
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Tsung-Hsien Wen
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Steve Young
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Negotiation of Antibiotic Treatment in Medical Consultations: A Corpus Based Study
Nan Wang
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Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures
Wenqiang Lei
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Xisen Jin
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Min-Yen Kan
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Zhaochun Ren
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Xiangnan He
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Dawei Yin
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IBM’s Belief Tracker: Results On Dialog State Tracking Challenge Datasets
Rudolf Kadlec
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Jindřich Libovický
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Jan Macek
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Jan Kleindienst
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The SJTU System for Dialog State Tracking Challenge 2
Kai Sun
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Lu Chen
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Su Zhu
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Kai Yu
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Cost-Sensitive Active Learning for Dialogue State Tracking
Kaige Xie
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Cheng Chang
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Liliang Ren
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Lu Chen
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Kai Yu
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http://research.microsoft.com/en-us/events/dstc/
Field Of Study
Task
Language Understanding
Approach
Deep Learning
Language
English
Dataset
Spoken Dialog
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