Reducing working memory load in spoken dialogue systems

Wolters, Maria; Georgila, Kallirroi; Moore, Johanna D.; Logie, Robert H.; MacPherson, Sarah E.; Watson, Matthew

doi:10.1016/j.intcom.2009.05.009

Cited by 47 publications

(25 citation statements)

References 77 publications

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“…In this case, we will use the heuristic information of the datábase and a set of rules to modify the default valúes specified by the designer in the first stages of the design. Another idea is to extend the user profiles (for instance to young/old people), in order to modify the valúes of several parameters for confirmation/presentation of information following the results reported in (Wolters et al, 2009). …”

Section: Discussionmentioning

confidence: 99%

Design and evaluation of acceleration strategies for speeding up the development of dialog applications

D’Haro

Córdoba

San-Segundo

et al. 2011

Speech Communication

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In this paper, we describe a complete development platform that features difíerent innovative acceleration strategies, not included in any other current platform, that simplify and speed up the definition of the difíerent elements required to design a spoken dialog service. The proposed accelerations are mainly based on using the information from the backend datábase schema and contents, as well as cumulative information produced throughout the difíerent steps in the design. Thanks to these accelerations, the interaction between the designer and the platform is improved, and in most cases the design is reduced to simple confirmations of the "proposals" that the platform dynamically pro vides at each step.In addition, the platform provides several other accelerations such as configurable templates that can be used to define the difíerent tasks in the service or the dialogs to obtain or show information to the user, automatic proposals for the best way to request slot contents from the user (i.e. using mixed-initiative forms or directed forms), an assistant that offers the set of more probable actions required to complete the definition of the difíerent tasks in the application, or another assistant for solving specific modality details such as confirmations of user answers or how to present them the lists of retrieved results after querying the backend datábase. Additionally, the platform also allows the creation of speech grammars and prompts, datábase access functions, and the possibility of using mixed initiative and over-answering dialogs. In the paper we also describe in detail each assistant in the platform, emphasizing the difíerent kind of methodologies followed to facilitate the design process at each one.Finally, we describe the results obtained in both a subjective and an objective evaluation with difíerent designers that confirm the viability, usefulness, and functionality of the proposed accelerations. Thanks to the accelerations, the design time is reduced in more than 56% and the number of keystrokes by 84%.

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Section: Discussionmentioning

confidence: 99%

Design and evaluation of acceleration strategies for speeding up the development of dialog applications

D’Haro

Córdoba

San-Segundo

et al. 2011

Speech Communication

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“…Furthermore, explicit repetition (by the system and/or by the user) decreases the efficiency of the interaction, as it increases the number of speech turns necessary to complete the task at hand (e.g., Wolters et al, 2009), potentially overloading the users' memory. The results of the current study are discussed below in light of these pros and cons.…”

Section: Theoretical Background: Dialogue Memory In Human-human Intermentioning

confidence: 99%

Explicit feedback from users attenuates memory biases in human-system dialogue

Knutsen

Bigot

Ros

2017

International Journal of Human-Computer Studies

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In human-human dialogue, the way in which a piece of information is added to the partners' common ground (i.e., presented and accepted) constitutes an important determinant of subsequent dialogue memory. The aim of this study was to determine whether this is also the case in human-system dialogue. An experiment was conducted in which naïve participants and a simulated dialogue system took turns to present references to various landmarks featured on a list. The kind of feedback used to accept these references (verbatim repetition vs. implicit acceptance) was manipulated. The participants then performed a recognition test during which they attempted to identify the references mentioned previously. Self-presented references were recognised better than references presented by the system; however, such presentation bias was attenuated when the initial presentation of these references was followed by verbatim repetition. Implications for the design of automated dialogue systems are discussed.

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“…Systems can also adapt to the user environment, as in the case of Ambient Intelligence applications [25,169]. A more sophisticated approach is to adapt the system to the user specifi knowledge and expertise, in which case the main research topics are the adaptation of systems to proficien y in the interaction language [112], age [161], different user expertise levels [49], and special needs [96]. Despite their complexity, these characteristics are to some extent rather static.…”

Section: Related Workmentioning

confidence: 99%

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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Reducing working memory load in spoken dialogue systems

Cited by 47 publications

References 77 publications

Design and evaluation of acceleration strategies for speeding up the development of dialog applications

Design and evaluation of acceleration strategies for speeding up the development of dialog applications

Explicit feedback from users attenuates memory biases in human-system dialogue

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

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