Multi-domain spoken dialogue system with extensibility and robustness against speech recognition errors

Authors:
Kazunori Komatani;Naoyuki Kanda;Mikio Nakano;Kazuhiro Nakadai;Hiroshi Tsujino;Tetsuya Ogata;Hiroshi G. Okuno
Affiliations:
Kyoto University, Sakyo, Kyoto, Japan;Kyoto University, Sakyo, Kyoto, Japan;Honda Research Institute Japan Co., Ltd., Wako, Saitama, Japan;Honda Research Institute Japan Co., Ltd., Wako, Saitama, Japan;Honda Research Institute Japan Co., Ltd., Wako, Saitama, Japan;Kyoto University, Sakyo, Kyoto, Japan;Kyoto University, Sakyo, Kyoto, Japan
Venue:
SigDIAL '06 Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue
Year:
2009

Citing 4
Cited 5

C4.5: programs for machine learning

C4.5: programs for machine learning
User Modeling in Spoken Dialogue Systems to Generate Flexible Guidance

User Modeling and User-Adapted Interaction
The LIMSI ARISE system for train travel information

ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
Confidence measures for dialogue management in the CU Communicator system

ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02

Integrating Topic Estimation and Dialogue History for Domain Selection in Multi-domain Spoken Dialogue Systems

IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Managing out-of-grammar utterances by topic estimation with domain extensibility in multi-domain spoken dialogue systems

Speech Communication
Example-based dialog modeling for practical multi-domain dialog system

Speech Communication
A framework for building conversational agents based on a multi-expert model

SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
A two-stage domain selection framework for extensible multi-domain spoken dialogue systems

SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference

Quantified Score

Hi-index	0.00

Visualization

Abstract

We developed a multi-domain spoken dialogue system that can handle user requests across multiple domains. Such systems need to satisfy two requirements: extensibility and robustness against speech recognition errors. Extensibility is required to allow for the modification and addition of domains independent of other domains. Robustness against speech recognition errors is required because such errors are inevitable in speech recognition. However, the systems should still behave appropriately, even when their inputs are erroneous. Our system was constructed on an extensible architecture and is equipped with a robust and extensible domain selection method. Domain selection was based on three choices: (I) the previous domain, (II) the domain in which the speech recognition result can be accepted with the highest recognition score, and (III) other domains. With the third choice we newly introduced, our system can prevent dialogues from continuously being stuck in an erroneous domain. Our experimental results, obtained with 10 subjects, showed that our method reduced the domain selection errors by 18.3%, compared to a conventional method.