13,722 research outputs found
A Plan-Based Model for Response Generation in Collaborative Task-Oriented Dialogues
This paper presents a plan-based architecture for response generation in
collaborative consultation dialogues, with emphasis on cases in which the
system (consultant) and user (executing agent) disagree. Our work contributes
to an overall system for collaborative problem-solving by providing a
plan-based framework that captures the {\em Propose-Evaluate-Modify} cycle of
collaboration, and by allowing the system to initiate subdialogues to negotiate
proposed additions to the shared plan and to provide support for its claims. In
addition, our system handles in a unified manner the negotiation of proposed
domain actions, proposed problem-solving actions, and beliefs proposed by
discourse actions. Furthermore, it captures cooperative responses within the
collaborative framework and accounts for why questions are sometimes never
answered.Comment: 8 pages, to appear in the Proceedings of AAAI-94. LaTeX source file,
requires aaai.sty and epsf.tex. Figures included in separate file
Modelling Users, Intentions, and Structure in Spoken Dialog
We outline how utterances in dialogs can be interpreted using a partial first
order logic. We exploit the capability of this logic to talk about the truth
status of formulae to define a notion of coherence between utterances and
explain how this coherence relation can serve for the construction of AND/OR
trees that represent the segmentation of the dialog. In a BDI model we
formalize basic assumptions about dialog and cooperative behaviour of
participants. These assumptions provide a basis for inferring speech acts from
coherence relations between utterances and attitudes of dialog participants.
Speech acts prove to be useful for determining dialog segments defined on the
notion of completing expectations of dialog participants. Finally, we sketch
how explicit segmentation signalled by cue phrases and performatives is covered
by our dialog model.Comment: 17 page
Building a robust dialogue system with limited data
We describe robustness techniques used in the CommandTalk system at the recognition level, the parsing level, and th dia6ue level, and how these were influenced by the lack of domain data. We used interviews with subject matter experts (SME's) to develop a single grammar for recognition, understanding, and generation, thus eliminating the need for a robust parser. We broadened the coverage of the recognition grammar by allowing word insertions and deletions, and we implemented clarification and correction subdialogues to increase robustness at tte dialogue level. We discuss the applicability of these techniques to other domains
Inferring Acceptance and Rejection in Dialogue by Default Rules of Inference
This paper discusses the processes by which conversants in a dialogue can
infer whether their assertions and proposals have been accepted or rejected by
their conversational partners. It expands on previous work by showing that
logical consistency is a necessary indicator of acceptance, but that it is not
sufficient, and that logical inconsistency is sufficient as an indicator of
rejection, but it is not necessary. I show how conversants can use information
structure and prosody as well as logical reasoning in distinguishing between
acceptances and logically consistent rejections, and relate this work to
previous work on implicature and default reasoning by introducing three new
classes of rejection: {\sc implicature rejections}, {\sc epistemic rejections}
and {\sc deliberation rejections}. I show how these rejections are inferred as
a result of default inferences, which, by other analyses, would have been
blocked by the context. In order to account for these facts, I propose a model
of the common ground that allows these default inferences to go through, and
show how the model, originally proposed to account for the various forms of
acceptance, can also model all types of rejection.Comment: 37 pages, uses fullpage, lingmacros, name
Improvising Linguistic Style: Social and Affective Bases for Agent Personality
This paper introduces Linguistic Style Improvisation, a theory and set of
algorithms for improvisation of spoken utterances by artificial agents, with
applications to interactive story and dialogue systems. We argue that
linguistic style is a key aspect of character, and show how speech act
representations common in AI can provide abstract representations from which
computer characters can improvise. We show that the mechanisms proposed
introduce the possibility of socially oriented agents, meet the requirements
that lifelike characters be believable, and satisfy particular criteria for
improvisation proposed by Hayes-Roth.Comment: 10 pages, uses aaai.sty, lingmacros.sty, psfig.st
Utilizing Statistical Dialogue Act Processing in Verbmobil
In this paper, we present a statistical approach for dialogue act processing
in the dialogue component of the speech-to-speech translation system \vm.
Statistics in dialogue processing is used to predict follow-up dialogue acts.
As an application example we show how it supports repair when unexpected
dialogue states occur.Comment: 6 pages; compressed and uuencoded postscript file; to appear in
ACL-9
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