Effective patient–clinician interaction to improve treatment outcomes for patients with psychosis: a mixed-methods design [PDF]
, 2017 BACKGROUND:At least 100,000 patients with schizophrenia receive care from community mental health teams (CMHTs) in England. These patients have regular meetings with clinicians, who assess them, engage them in treatment and co-ordinate care.
Eldridge, S. +8 more
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Learning End-to-End Goal-Oriented Dialog with Multiple Answers
, 2018 In a dialog, there can be multiple valid next utterances at any point. The present end-to-end neural methods for dialog do not take this into account. They learn with the assumption that at any time there is only one correct next utterance. In this work,
Ganhotra, Jatin +3 more
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Tracking of enriched dialog states for flexible conversational information access
, 2018 Dialog state tracking (DST) is a crucial component in a task-oriented dialog system for conversational information access. A common practice in current dialog systems is to define the dialog state by a set of slot-value pairs.
Dai, Yinpei +3 more
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Contextual Out-of-Domain Utterance Handling With Counterfeit Data Augmentation
, 2019 Neural dialog models often lack robustness to anomalous user input and produce inappropriate responses which leads to frustrating user experience. Although there are a set of prior approaches to out-of-domain (OOD) utterance detection, they share a few ...
Lee, Sungjin, Shalyminov, Igor
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An End-to-End Trainable Neural Network Model with Belief Tracking for Task-Oriented Dialog
, 2017 We present a novel end-to-end trainable neural network model for task-oriented dialog systems. The model is able to track dialog state, issue API calls to knowledge base (KB), and incorporate structured KB query results into system responses to ...
Lane, Ian, Liu, Bing
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Incremental LSTM-based Dialog State Tracker
, 2015 A dialog state tracker is an important component in modern spoken dialog systems. We present an incremental dialog state tracker, based on LSTM networks. It directly uses automatic speech recognition hypotheses to track the state. We also present the key
Jurcicek, Filip, Zilka, Lukas
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Optimizing human-interpretable dialog management policy using Genetic Algorithm
, 2015 Automatic optimization of spoken dialog management policies that are robust to environmental noise has long been the goal for both academia and industry. Approaches based on reinforcement learning have been proved to be effective.
Ren, Hang, Xu, Weiqun, Yan, Yonghong
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An Open-Domain Dialog Act Taxonomy [PDF]
, 2008 This document defines the taxonomy of dialog acts that are necessary to encode domain-independent dialog moves in the context of a task-oriented, open-domain dialog.
Bisazza, Arianna +3 more
core
SimDialog: A visual game dialog editor [PDF]
, 2008 SimDialog is a visual editor for dialog in computer games. This paper presents the design of SimDialog, illustrating how script writers and non-programmers can easily create dialog for video games with complex branching structures and dynamic response ...
Biocca, F. +3 more
core
Bootstrapping Multilingual Intent Models via Machine Translation for Dialog Automation [PDF]
, 2018 With the resurgence of chat-based dialog systems in consumer and enterprise applications, there has been much success in developing data-driven and rule-based natural language models to understand human intent. Since these models require large amounts of
Bangalore, Srinivas +2 more
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