Spoken Dialog Challenge 2010

Black, Alan W.; Burger, Susanne; Langner, Brian; Parent, Gabriel; Eskénazi, Maxine

doi:10.1109/slt.2010.5700894

Cited by 34 publications

(26 citation statements)

References 2 publications

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“…Initial evaluations of the system indicate that the BUD-SLETSGO system does outperform the BASELINE, as well as the other systems entered into the challenge [10]. Compared to the BASELINE system, the BUDSLETSGO system improves the dialogue success rate by 24.5% and the word error rate by 9.7%.…”

Section: Resultsmentioning

confidence: 99%

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Bayesian dialogue system for the Let's Go Spoken Dialogue Challenge

Thomson¹,

Yu²,

Keizer³

et al. 2010

2010 IEEE Spoken Language Technology Workshop

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This paper describes how Bayesian updates of dialogue state can be used to build a bus information spoken dialogue system. The resulting system was deployed as part of the 2010 Spoken Dialogue Challenge. The purpose of this paper is to describe the system, and provide both simulated and human evaluations of its performance. In control tests by human users, the success rate of the system was 24.5% higher than the baseline Lets Go! system.

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Section: Resultsmentioning

confidence: 99%

“…spoken dialogue challenge. A complete description of the challenge and the control tests is given in [10]. During the control tests, each site taking part in the challenge was asked to find test volunteers.…”

Section: Human Evaluationmentioning

confidence: 99%

Bayesian dialogue system for the Let's Go Spoken Dialogue Challenge

Thomson¹,

Yu²,

Keizer³

et al. 2010

2010 IEEE Spoken Language Technology Workshop

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“…Table IV shows further details about the success rate of the system in both weeks. The evaluation measures used in the Spoken Dialog Challenge [13] enable us to compare the performance of our system with the systems that were run in the SDC on a similar task.…”

Section: Resultsmentioning

confidence: 99%

Towards choosing better primes for spoken dialog systems

Lopes

Eskénazi

Trancoso

2011

2011 IEEE Workshop on Automatic Speech Recognition &Amp; Understanding

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Abstract-When humans and computers use the same terms (primes, when they entrain to one another), spoken dialogs proceed more smoothly. The goal of this paper is to describe initial steps we have found that will enable us to eventually automatically choose better primes in spoken dialog system prompts. Two different sets of prompts were used to understand what makes one prime more suitable than another. The impact of the primes chosen in speech recognition was evaluated. In addition, results reveal that users did adopt the new vocabulary introduced in the new system prompts. As a result of this, performance of the system improved, providing clues for the trade off needed when choosing between adequate primes in prompts and speech recognition performance.

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“…In 2009, a corpus of 338 dialogs acquired with real users was distributed among the scientific community as a common testbed for the 2010 Spoken Dialog Challenge initiative (100). The aim of the Challenge was to bring together multiple implementations of the same dialog task and deploy them in uncontrolled real user conditions and then make the results available for common evaluation techniques.…”

Section: Application To the Let's Go Dialog Systemmentioning

confidence: 99%

A proposal for the development of adaptive spoken interfaces to access the Web

2015

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Spoken dialog systems have been proposed as a solution to facilitate a more natural human machine interaction. In this paper, we propose a framework to model the user's intention during the dialog and adapt the dialog model dynamically to the user needs and preferences, thus developing more efficient, adapted, and usable spoken dialog systems. Our framework employs statistical models based on neural networks that take into account the history of the dialog up to the current dialog state in order to predict the user's intention and the next system response. We describe our proposal and detail its application in the Let's Go spoken dialog system.

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Spoken Dialog Challenge 2010

Cited by 34 publications

References 2 publications

Bayesian dialogue system for the Let's Go Spoken Dialogue Challenge

Bayesian dialogue system for the Let's Go Spoken Dialogue Challenge

Towards choosing better primes for spoken dialog systems

A proposal for the development of adaptive spoken interfaces to access the Web

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