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A Case Study of Applying Decision Theory in the Real World: POMDPs and Spoken Dialog Systems

A Case Study of Applying Decision Theory in the Real World: POMDPs and Spoken Dialog Systems

Jason D. Williams
Copyright: © 2012 |Pages: 28
ISBN13: 9781609601652|ISBN10: 1609601653|EISBN13: 9781609601676
DOI: 10.4018/978-1-60960-165-2.ch014
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MLA

Williams, Jason D. "A Case Study of Applying Decision Theory in the Real World: POMDPs and Spoken Dialog Systems." Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions, edited by L. Enrique Sucar, et al., IGI Global, 2012, pp. 315-342. https://doi.org/10.4018/978-1-60960-165-2.ch014

APA

Williams, J. D. (2012). A Case Study of Applying Decision Theory in the Real World: POMDPs and Spoken Dialog Systems. In L. Sucar, E. Morales, & J. Hoey (Eds.), Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions (pp. 315-342). IGI Global. https://doi.org/10.4018/978-1-60960-165-2.ch014

Chicago

Williams, Jason D. "A Case Study of Applying Decision Theory in the Real World: POMDPs and Spoken Dialog Systems." In Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions, edited by L. Enrique Sucar, Eduardo F. Morales, and Jesse Hoey, 315-342. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-60960-165-2.ch014

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Abstract

Spoken dialog systems present a classic example of planning under uncertainty. Speech recognition errors are ubiquitous and impossible to detect reliably, so the state of the conversation can never be known with certainty. Despite this, the system must choose actions to make progress to a long term goal. As such, decision theory, and in particular partially-observable Markov decision processes (POMDPs), present an attractive approach to building spoken dialog systems. Initial work on “toy” dialog systems validated the benefits of the POMDP approach; however, it also found that straightforward application of POMDPs could not scale to real-world problems. Subsequent work by a number of research teams has scaled up planning and belief monitoring, incorporated high-fidelity user simulations, and married commercial development practices with automatic optimization. Today, statistical dialog systems are being fielded by research labs for public use. This chapter traces the history of POMDP-based spoken dialog systems, and sketches avenues for future work.

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