Assessment of dialogue systems by means of a new simulation technique

López-Cózar, Ramón; Torre, Ángel de la; Segura, José C.; Rubio, Antonio J.

doi:10.1016/s0167-6393(02)00126-7

Cited by 69 publications

(48 citation statements)

References 9 publications

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“…This approach was firs used by [84] and has been adopted in later work on user simulation by most research groups [42,54,119,136]. Modeling interaction on the intention-level avoids the need to reproduce the enormous variety of human language on the level of speech signals [8,158] or word sequences [53,87].…”

Section: Modeling the User Intentionmentioning

confidence: 99%

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Modeling the user state for context-aware spoken interaction in ambient assisted living

2014

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Ambient Assisted Living (AAL) systems must provide adapted services easily accessible by a wide variety of users. This can only be possible if the communication between the user and the system is carried out through an interface that is simple, rapid, effective, and robust. Natural language interfaces such as dialog systems fulfil these requisites, as they are based on a spoken conversation that resembles human communication. In this paper, we enhance systems interacting in AAL domains by means of incorporating context-aware conversational agents that consider the external context of the interaction and predict the user's state. The user's state is built on the basis of their emotional state and intention, and it is recognized by means of a module conceived as an intermediate phase between natural language understanding and dialog management in the architecture of the conversational agent. This prediction, carried out for each user turn in the dialog, makes it possible to adapt the system dynamically to the user's needs. We have evaluated our proposal developing a context-aware system adapted to patients suffering from chronic pulmonary diseases, and provide a detailed discussion of the positive influenc of our proposal in the success of the interaction, the information and services provided, as well as the perceived quality.

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Section: Modeling the User Intentionmentioning

confidence: 99%

“…In a rule-based user model, different rules determine the behavior of the system [40,87]. In this approach the researcher has complete control over the design of the evaluation study.…”

Section: Modeling the User Intentionmentioning

confidence: 99%

Modeling the user state for context-aware spoken interaction in ambient assisted living

2014

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“…López-Cózar et al (2003) develop a user model for a dialog system in the domain of fastfood ordering. Actions are selected by a number of rules describing expected behavior for each system question, given a goal and the correctness of the information confirmed by the system.…”

Section: User Simulation For Spoken Dialog Systemsmentioning

confidence: 99%

Analysis of a new simulation approach to dialog system evaluation

Engelbrecht

Quade

Möller

2009

Speech Communication

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“…In our vision of a simulated environment, communication between modules takes place at the intention level rather than at the word sequence or speech signal level, as it would be in real-world applications and like proposed in [5]. We regard an intention as the minimal unit of information that a dialogue participant can express independently.…”

Section: Intention-based Modelingmentioning

confidence: 99%

“…The second type of methods intends to be more task-independent by integrating models of each component of a SDS including the speech processing systems but also the user like depicted on Figure 1. Although it makes use of a complex modular simulation environment, the method presented in [5] stays very task-dependent and even system-dependent since it requires recordings of spoken utterances collected during real interactions and real implementations of speech processing systems such as an Automatic Speech Recognition (ASR) system. It is therefore out of the scope of this paper and we will focus on generic simulation methods [4][6] [7] considering the dialogue at the intention level (see section 2.1) and not at the acoustic level like in [5].…”

Section: Introductionmentioning

confidence: 99%

Consistent Goal-Directed User Model for Realisitc Man-Machine Task-Oriented Spoken Dialogue Simulation

Pietquin

2006

2006 IEEE International Conference on Multimedia and Expo

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Because of the great variability of factors to take into account, designing a spoken dialogue system is still a tailoring task. Rapid design and reusability of previous work is made very difficult. For these reasons, the application of machine learning methods to dialogue strategy optimization has become a leading subject of researches this last decade. Yet, techniques such as reinforcement learning are very demanding in training data while obtaining a substantial amount of data in the particular case of spoken dialogues is time-consuming and therefore expansive. In order to expand existing data sets, dialogue simulation techniques are becoming a standard solution.In this paper we describe a user modeling technique for realistic simulation of man-machine goal-directed spoken dialogues. This model, based on a stochastic description of man-machine communication, unlike previously proposed models, is consistent along the interaction according to its history and a predefined user goal.

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Assessment of dialogue systems by means of a new simulation technique

Cited by 69 publications

References 9 publications

Modeling the user state for context-aware spoken interaction in ambient assisted living

Modeling the user state for context-aware spoken interaction in ambient assisted living

Analysis of a new simulation approach to dialog system evaluation

Consistent Goal-Directed User Model for Realisitc Man-Machine Task-Oriented Spoken Dialogue Simulation

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