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Bootstrapping spoken dialogue systems by exploiting reusable libraries

Published online by Cambridge University Press:  01 July 2008

GIUSEPPE DI FABBRIZIO ,
GOKHAN TUR ,
DILEK HAKKANI-TÜR ,
MAZIN GILBERT ,
BERNARD RENGER ,
DAVID GIBBON ,
ZHU LIU  and
BEHZAD SHAHRARAY
GIUSEPPE DI FABBRIZIO
Affiliation:
AT&T Labs—Research, 180 Park Avenue, Florham Park, NJ 07932, USA e-mail: pino@research.att.com, gtur@research.att.com, dtur@research.att.com, mazin@research.att.com, renger@research.att.com
GOKHAN TUR
Affiliation:
AT&T Labs—Research, 180 Park Avenue, Florham Park, NJ 07932, USA e-mail: pino@research.att.com, gtur@research.att.com, dtur@research.att.com, mazin@research.att.com, renger@research.att.com
DILEK HAKKANI-TÜR
Affiliation:
AT&T Labs—Research, 180 Park Avenue, Florham Park, NJ 07932, USA e-mail: pino@research.att.com, gtur@research.att.com, dtur@research.att.com, mazin@research.att.com, renger@research.att.com
MAZIN GILBERT
Affiliation:
AT&T Labs—Research, 180 Park Avenue, Florham Park, NJ 07932, USA e-mail: pino@research.att.com, gtur@research.att.com, dtur@research.att.com, mazin@research.att.com, renger@research.att.com
BERNARD RENGER
Affiliation:
AT&T Labs—Research, 180 Park Avenue, Florham Park, NJ 07932, USA e-mail: pino@research.att.com, gtur@research.att.com, dtur@research.att.com, mazin@research.att.com, renger@research.att.com
DAVID GIBBON
Affiliation:
AT&T Labs—Research, 200 Laurel Avenue South, Middletown, NJ 07748, USA e-mail: dcg@research.att.com, zliu@research.att.com, behzad@research.att.com
ZHU LIU
Affiliation:
AT&T Labs—Research, 200 Laurel Avenue South, Middletown, NJ 07748, USA e-mail: dcg@research.att.com, zliu@research.att.com, behzad@research.att.com
BEHZAD SHAHRARAY
Affiliation:
AT&T Labs—Research, 200 Laurel Avenue South, Middletown, NJ 07748, USA e-mail: dcg@research.att.com, zliu@research.att.com, behzad@research.att.com
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Abstract

Building natural language spoken dialogue systems requires large amounts of human transcribed and labeled speech utterances to reach useful operational service performances. Furthermore, the design of such complex systems consists of several manual steps. The User Experience (UE) expert analyzes and defines by hand the system core functionalities: the system semantic scope (call-types) and the dialogue manager strategy that will drive the human–machine interaction. This approach is extensive and error-prone since it involves several nontrivial design decisions that can be evaluated only after the actual system deployment. Moreover, scalability is compromised by time, costs, and the high level of UE know-how needed to reach a consistent design. We propose a novel approach for bootstrapping spoken dialogue systems based on the reuse of existing transcribed and labeled data, common reusable dialogue templates, generic language and understanding models, and a consistent design process. We demonstrate that our approach reduces design and development time while providing an effective system without any application-specific data.

Type
Papers
Information
Natural Language Engineering , Volume 14 , Issue 3 , July 2008 , pp. 313 - 335
Copyright
Copyright © Cambridge University Press 2007

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