Conference Paper

Let's go public! taking a spoken dialog system to the real world.

Conference: INTERSPEECH 2005 - Eurospeech, 9th European Conference on Speech Communication and Technology, Lisbon, Portugal, September 4-8, 2005
Source: DBLP

ABSTRACT In this paper, we describe how a research spoken dialog system was made available to the general public. The Let's Go Public spoken dialog system provides bus schedule information to the Pittsburgh population during off-peak times. This paper describes the changes necessary to make the system usable for the general public and presents analysis of the calls and strategies we have used to ensure high performance.

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    • "Our experiments are based on the Let's Go corpus (Raux et al., 2005). Let's Go contains recorded interactions between a spoken dialogue system and human users who make enquiries about the bus schedule in Pittsburgh. "
    SIGDIAL; 01/2013
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    • "The context was the Noctívago system, an experimental agenda-based SDS in European Portuguese that provides schedule information about night buses in Lisbon. The first version of the system was adapted from Let's Go [7], a live system that gives bus schedule information for real users in Pittsburgh since 2005. Both telephone systems were based on the Olympus open-source architecture for SDSs [8], and used Ravenclaw [9], an agenda-based dialog manager. "
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    ABSTRACT: This paper proposes an approach to the use of lexical entrainment in Spoken Dialog Systems. This approach aims to increase the dialog success rate by adapting the lexical choices of the system to the user's lexical choices. If the system finds that the users lexical choice degrades the performance, it will try to establish a new conceptual pact, proposing other words that the user may adopt, in order to be more successful in task completion. The approach was implemented and tested in two different systems. Tests showed a relative dialog estimated error rate reduction of 10% and a relative reduction in the average number of turns per session of 6%.
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on; 01/2013
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    • "Dialogue Systems are a field of Computer Science that focuses on the construction of computer systems that interact with human users via natural-language dialogues. Much of the work in this area is focused on systems that obtain information or search databases such as querying bus schedules (Raux et al. 2005) and booking airline tickets (Rudnicky et al. 1999). In recent years, RL has been widely applied to the design of dialogue systems (Williams et al. 2005; Walker 2000; Singh et al. 2002). "
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    ABSTRACT: For many forms of e-learning environments, the system’s behavior can be viewed as a sequential decision process wherein, at each discrete step, the system is responsible for selecting the next action to take. Pedagogical strategies are policies to decide the next system action when there are multiple ones available. In this project we present a Reinforcement Learning (RL) approach for inducing effective pedagogical strategies and empirical evaluations of the induced strategies. This paper addresses the technical challenges in applying RL to Cordillera, a Natural Language Tutoring System teaching students introductory college physics. The algorithm chosen for this project is a model-based RL approach, Policy Iteration, and the training corpus for the RL approach is an exploratory corpus, which was collected by letting the system make random decisions when interacting with real students. Overall, our results show that by using a rather small training corpus, the RL-induced strategies indeed measurably improved the effectiveness of Cordillera in that the RL-induced policies improved students’ learning gains significantly.
    User Modeling and User-Adapted Interaction 04/2011; 21:137-180. DOI:10.1007/s11257-010-9093-1 · 1.93 Impact Factor


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