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

• Published in: IEEE 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
• Language: English
• 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
• ISSN: 1932-4553; 1941-0484
• DOI: 10.1109/JSTSP.2012.2229692

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.