An Example-Based Approach to Ranking Multiple Dialog States for Flexible Dialog Management

This paper presents a new hybrid dialog management framework that integrates a statistical ranking algorithm into an example-based dialog management approach for chat-like dialogs. The proposed model uses ranking features that consider various aspects of dialogs, including the relative importance of...

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Published inIEEE journal of selected topics in signal processing Vol. 6; no. 8; pp. 943 - 958
Main Authors Hyungjong Noh, Seonghan Ryu, Donghyeon Lee, Kyusong Lee, Cheongjae Lee, Lee, G. G.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.12.2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Aggregates
Algorithms
Context
Dialog management
Human computer interaction
Learning
Management
Mathematical models
Natural languages
Ranking
Robustness
Speech
spoken dialog system
Students
Studies
User interfaces
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Abstract This paper presents a new hybrid dialog management framework that integrates a statistical ranking algorithm into an example-based dialog management approach for chat-like dialogs. The proposed model uses ranking features that consider various aspects of dialogs, including the relative importance of speech acts, dialog history sequences, and the causal relationships among speech acts and slot-filling states. The ranking algorithm enables one to aggregate these feature scores systematically and to generate diverse system responses. Additionally, the model provides detailed feedback by analyzing the causal relationships among speech acts and predicting the user's possible intentions associated with a given dialog states. Simulated experimental results demonstrate that our approach is effective for task-oriented dialogs and chat-like dialogs. Additionally, a case study using elementary school students implies that the proposed system can be used for language learning purposes in addition to task-oriented services.
AbstractList This paper presents a new hybrid dialog management framework that integrates a statistical ranking algorithm into an example-based dialog management approach for chat-like dialogs. The proposed model uses ranking features that consider various aspects of dialogs, including the relative importance of speech acts, dialog history sequences, and the causal relationships among speech acts and slot-filling states. The ranking algorithm enables one to aggregate these feature scores systematically and to generate diverse system responses. Additionally, the model provides detailed feedback by analyzing the causal relationships among speech acts and predicting the user's possible intentions associated with a given dialog states. Simulated experimental results demonstrate that our approach is effective for task-oriented dialogs and chat-like dialogs. Additionally, a case study using elementary school students implies that the proposed system can be used for language learning purposes in addition to task-oriented services.
Author Kyusong Lee
Cheongjae Lee
Seonghan Ryu
Hyungjong Noh
Donghyeon Lee
Lee, G. G.
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SubjectTerms Aggregates
Algorithms
Context
Dialog management
Human computer interaction
Learning
Management
Mathematical models
Natural languages
Ranking
Robustness
Speech
spoken dialog system
Students
Studies
User interfaces
Title An Example-Based Approach to Ranking Multiple Dialog States for Flexible Dialog Management
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