3,432 research outputs found
The Impact of Interpretation Problems on Tutorial Dialogue
Supporting natural language input may improve learning in intelligent tutoring systems. However, interpretation errors are unavoidable and require an effective recovery policy. We describe an evaluation of an error recovery policy in the BEE-TLE II tutorial dialogue system and discuss how different types of interpretation problems affect learning gain and user satisfaction. In particular, the problems arising from student use of non-standard terminology appear to have negative consequences. We argue that existing strategies for dealing with terminology problems are insufficient and that improving such strategies is important in future ITS research.
Robust Dialog Management Through A Context-centric Architecture
This dissertation presents and evaluates a method of managing spoken dialog interactions with a robust attention to fulfilling the human userâs goals in the presence of speech recognition limitations. Assistive speech-based embodied conversation agents are computer-based entities that interact with humans to help accomplish a certain task or communicate information via spoken input and output. A challenging aspect of this task involves open dialog, where the user is free to converse in an unstructured manner. With this style of input, the machineâs ability to communicate may be hindered by poor reception of utterances, caused by a userâs inadequate command of a language and/or faults in the speech recognition facilities. Since a speech-based input is emphasized, this endeavor involves the fundamental issues associated with natural language processing, automatic speech recognition and dialog system design. Driven by ContextBased Reasoning, the presented dialog manager features a discourse model that implements mixed-initiative conversation with a focus on the userâs assistive needs. The discourse behavior must maintain a sense of generality, where the assistive nature of the system remains constant regardless of its knowledge corpus. The dialog manager was encapsulated into a speech-based embodied conversation agent platform for prototyping and testing purposes. A battery of user trials was performed on this agent to evaluate its performance as a robust, domain-independent, speech-based interaction entity capable of satisfying the needs of its users
Incorporating a User Model to Improve Detection of Unhelpful Robot Answers
Dialogues with robots frequently exhibit social dialogue acts such as greeting, thanks, and goodbye. This opens the opportunity of using these dialogue acts for dialogue management, in particular for detecting misunderstandings. Our corpus analysis shows that the social dialogue acts have different scopes of their associations with the discourse features within the dialogue: greeting in the userâs first turn is associated with such distant, or global, features as the likelihood of having questions answered, persistence, and ending with bye. The userâs thanks turn, on the other hand, is strongly associated with the helpfulness of the preceding robotâs answer. We therefore interpret the greeting as a component of a user model that can provide information about the userâs traits and be associated with discourse features at various stages of the dialogue. We conduct a detailed analysis of the userâs thanking behavior and demonstrate that userâs thanks can be used in the detection of unhelpful robotâs answers. Incorporating the greeting information further improves the detection. We discuss possible applications of this work for human-robot dialogue management.
Spoken dialog systems based on online generated stochastic finite-state transducers
This is the authorâs version of a work that was accepted for publication in Speech Communication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Speech Communication 83 (2016) 81â93. DOI 10.1016/j.specom.2016.07.011.In this paper, we present an approach for the development of spoken dialog systems based on the statistical
modelization of the dialog manager. This work focuses on three points: the modelization of the
dialog manager using Stochastic Finite-State Transducers, an unsupervised way to generate training corpora,
and a mechanism to address the problem of coverage that is based on the online generation of
synthetic dialogs. Our proposal has been developed and applied to a sport facilities booking task at the
university. We present experimentation evaluating the system behavior on a set of dialogs that was acquired
using the Wizard of Oz technique as well as experimentation with real users. The experimentation
shows that the method proposed to increase the coverage of the Dialog System was useful to find new
valid paths in the model to achieve the user goals, providing good results with real users.
Š 2016 Elsevier B.V. All rights reserved.This work is partially supported by the project ASLP-MULAN: Audio, Speech and Language Processing for Multimedia Analytics (MINECO TIN2014-54288-C4-3-R).Hurtado Oliver, LF.; Planells Lerma, J.; Segarra Soriano, E.; SanchĂs Arnal, E. (2016). Spoken dialog systems based on online generated stochastic finite-state transducers. Speech Communication. 83:81-93. https://doi.org/10.1016/j.specom.2016.07.011S81938
Evaluation of ECA Gesture strategies for robust Human-Computer Interaction
Embodied Conversational Agents (ECAs) offer us the possibility to design pleasant and efficient human-machine interaction. In this paper we present an evaluation scheme to compare dialogue-based speaker authentication and information retrieval systems with and without ECAs on the interface. We used gestures and other visual cues to improve fluency and robustness of interaction with these systems. Our tests results suggest that when an ECA is present users perceive fewer system errors, their frustration levels are lower, turn-changing goes more smoothly, the interaction experience is more enjoyable, and system capabilities are generally perceived more positively than when no ECA is present. However, the ECA seems to intensify the users' privacy concerns
Seeing the big PICTURE: A framework for improving the communication of requirements within the Business-IT relationship
The relationship between the business and IT departments in the context of the organisation has been characterised as highly divisive. Contributing problems appear to revolve around the failure to adequately communicate and understand the required information for the alignment of business and IT strategies and infrastructures. This study takes a communication-based view on the concept of alignment, in terms of the relationship between the retail business and IT within a major high street UK bank. A research framework (PICTURE) is used to provide insight into this relationship and guide the analysis of interviews with 29 individuals on mid-high management level for their thematic content. The paper highlights the lessons that can be derived from the study of the BIT relationship and how possible improvements could be made
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