Repairing conversational misunderstandings and non-understandings

Hirst, Graeme; McRoy, Susan; Heeman, Peter A.; Edmonds, Philip; Horton, Diane

doi:10.1016/0167-6393(94)90073-6

Cited by 58 publications

(35 citation statements)

References 11 publications

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“…to more detailed requests, such as "Where should the pipe go?" Consistent with prior work that associated confusion with not understanding and clarification with misunderstanding [8,12,16], we classified requests into the categories confusion, confirmation, and clarification.…”

Section: B Analysismentioning

confidence: 74%

“…Despite the best efforts of instructors, there will inevitably be instances of breakdownsmisunderstandings or miscommunication concerning task goals-that can either impede ongoing progress or lead to breakdowns in the future [29]. To correct breakdowns, humans engage in repair, a process that allows participants to correct misunderstandings and helps ensure that all participants have a similar understanding of the relayed information [12,29]. The process of engaging in repair is often context-sensitive [21].…”

Section: A Instruction In Human-human Interactionmentioning

confidence: 99%

“…This repair is often context-specific in that it requires knowledge of prior actions and current expectations in order to succeed. Additionally, humans use a variety of techniques to repair breakdowns [12] and adapt their use of these techniques to the context of the interaction [20].…”

Section: Introductionmentioning

confidence: 99%

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Effective Task Training Strategies for Instructional Robots

Sauppé

Mutlu

2014

Robotics: Science and Systems X

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Abstract-From teaching in labs to training for assembly, a key role that robots are expected to play is to instruct their users in completing physical tasks. While task instruction requires a wide range of capabilities, such as effective use of verbal and nonverbal language, a fundamental requirement for an instructional robot is to provide its students with task instructions in a way that maximizes their understanding of and performance in the task. In this paper, we present an autonomous instructional robot system and investigate how different instructional strategies affect user performance and experience. We collected data on human instructor-trainee interactions in a pipe-assembly task. Our analysis identified two key instructional strategies: (1) grouping instructions together and (2) summarizing the outcome of subsequent instructions. We implemented these strategies into a humanlike robot that autonomously instructed its users in the same pipe-assembly task. To achieve autonomous instruction, we also developed a repair mechanism that enabled the robot to correct mistakes and misunderstandings. An evaluation of the instructional strategies in a human-robot interaction study showed that employing the grouping strategy resulted in faster task completion and increased rapport with the robot, although it also increased the number of task breakdowns. Our model of instructional strategies and study findings offer strong implications for the design of instructional robots.

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Section: B Analysismentioning

confidence: 74%

Section: A Instruction In Human-human Interactionmentioning

confidence: 99%

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Effective Task Training Strategies for Instructional Robots

Sauppé

Mutlu

2014

Robotics: Science and Systems X

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“…For example, and Hirst et al (1994) focused on miscommunication in spoken dialogue systems and Feild et al (2010) focused on user frustrations in search systems. In this paper, we focus on predicting the cause of errors among the different components in IAs.…”

Section: Error Analysis and Error Detectionmentioning

confidence: 99%

Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

2017

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We are excited to welcome you to this year's SIGdial Conference, the 18th Annual Meeting of the Special Interest Group on Discourse and Dialogue. We are pleased to hold the conference in Saarbrücken on August 15-17th, co-located with SemDial 2017, and in close proximity to both INTERSPEECH 2017 and YRRSDS 2017, the Young Researchers' Roundtable on Spoken Dialog Systems.The SIGdial conference remains a premier publication venue for research in discourse and dialogue. This year, the program includes oral presentations, poster sessions, and one demo session. SIGdial 2017 also hosts three special sessions, two joint with SemDial 2017.We received 113 submissions this year. In only one previous year has there been a greater number of submissions to SIGdial. All long and short papers received at least 3 reviews. We carefully considered both the numeric ratings and the tenor of the comments in making our selections for the program. Overall, the members of the Program Committee did an excellent job in reviewing the submitted papers. We thank them for their important role in selecting the accepted papers and for helping to come up with a high quality program for the conference. We also thank Pierre Lison, Mentoring Chair for SIGdial 2017, for his dedicated work on the mentoring process. The goal of mentoring is to assist authors of papers that contain important ideas but lack clarity. In line with the SIGdial tradition, our aim has been to create a balanced program that accommodates as many favorably rated papers as possible. We accepted 29 long papers, 11 short papers and 7 demo presentations. These numbers give an overall acceptance rate of 41.6%. The rates separately for types of papers are 42% for long papers, 30% for short and 87% for demo submissions. Of the long papers, 18 were presented as oral presentations. The remaining 11 long papers and all the short papers were presented as posters, split into two poster sessions.This year SIGdial has three special sessions on topics of growing interest. The chosen sessions were (i) the Special Session on Negotiation Dialog organized by Amanda Stent, Aasish Pappu, Diane Litman and Marilyn Walker; (ii) the Second WOCHAT Special Session on Chatbots and Conversational Agents organized by Ryuichiro Higashinaka, Ron Artstein, Rafael E. Banchs, and Wolfgang Minker; and (iii) Special Session on Natural Language Generation for Dialog Systems organized by Marilyn Walker, Verena Rieser, Vera Demberg, Dietrich Klakow, Dilek Hakkani-Tur, David M. Howcroft and Shereen Oraby. These specialized topics brought diverse paper submissions to our technical program. At the conference, the special sessions also featured panel discussions and position talks, allowing for active engagement of the conference participants. This year, two of these special sessions, the one on negotiation and on conversational agents, are part of the joint SIGdial/SemDial program at the conference bringing both communities to participate in them. This year's SIGdial conference runs 3 full days compared to previous year...

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“…A common distinction is made between misunderstanding and non-understanding (e.g. Hirst et al, 1994). Misunderstanding means that the addressee obtains an interpretation that is not in line with the speaker's intentions.…”

Section: Miscommunicationmentioning

confidence: 99%

Galatea: A Discourse Modeller Supporting Concept-Level Error Handling in Spoken Dialogue Systems

Skantze¹

Recent Trends in Discourse and Dialogue

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In this paper, a discourse modeller for conversational spoken dialogue systems, called GALATEA, is presented. Apart from handling the resolution of ellipses and anaphora, it tracks the "grounding status" of concepts that are mentioned during the discourse, i.e. information about who said what when. This grounding information also contains concept confidence scores that are derived from the speech recogniser word confidence scores. The discourse model may then be used for concept-level error handling, i.e. grounding of concepts, fragmentary clarification requests, and detection of erroneous concepts in the model at later stages in the dialogue.

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Repairing conversational misunderstandings and non-understandings

Cited by 58 publications

References 11 publications

Effective Task Training Strategies for Instructional Robots

Effective Task Training Strategies for Instructional Robots

Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

Galatea: A Discourse Modeller Supporting Concept-Level Error Handling in Spoken Dialogue Systems

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