ICT Workshop on Dialogue
Research
Research Talk Abstracts
Day
One: May 15, 2008
DICO:
Managing cognitive load in in-vehicle dialogue
Staffan Larsson, Gothenburg University
The overall purpose of the Dico project is to demonstrate how
state-of-the-art spoken language dialogue systems can enable access to
communication, entertainment and information services as well as to environment
control in vehicles. The use of dialogue systems in vehicles raises the problem
of making sure that the dialogue does not distract the driver from the primary
task of driving. Of course, flexible dialogue management is one way of
decreasing cognitive load; in DICO, we use the GoDiS dialogue manager (Larsson
2002). Concerning in-vehicle dialogue more specifically, earlier studies have
indicated that humans are very apt at adapting the dialogue to the traffic
situation and the cognitive load of the driver. A goal in DICO is therefore to investigate strategies for
managing cognitive load in in-vehicle dialogue. Results of these investigations
will be used as a basis for the development of dialogue strategies in future
version of the system.
Using
Degrees of Grounding for Dialogue Managment
Antonio
Roque, Graduate Research Assistant, USC
Abstract:
The
Degrees of Grounding model defines the extent to which material being discussed
in a dialogue has been grounded.
This model has been developed and evaluated by a corpus analysis, and
includes a set of types of evidence of understanding, a set of degrees of
groundedness, a set of grounding criteria, and methods for identifying each of
these. I describe how this model
can be used for dialogue management.
A Computational
Model of the Collaborative Use of Natural Language despite Private Uncertainty
in Dialogue
David Devault, PhD Student
University of Rutgers, Visiting Research Assistant, USC,
Abstract:
This dissertation is part
of a project to develop a detailed and robust computational model of natural
language dialogue that clarifies and reconciles the linguistic and collaborative
reasoning that interlocutors need to perform in conversation. This dissertation makes three primary
contributions to this project.
The first contribution is
a new lightweight theoretical model of natural language dialogue as a
collaboration between interlocutors. The new model weakens strict assumptions
about the alignment of interlocutor mental states in conversation that have
traditionally been seen as essential to capturing the collaborative aspects of
a speaker's linguistic choices (Clark and Marshall, 1981). By eliminating
strict assumptions about how interlocutors reason about each other's mental
states, our model significantly clarifies the methodological target of
collaborative language use in implemented dialogue systems that face real-world
uncertainties.
The second contribution is
a new theoretical approach to modeling the current state of a conversation as
an objective product of prior interlocutor action rather than a by-product of
the interlocutors' current mental states.
We illustrate this objective view of context using COREF, an implemented
dialogue system that collaboratively identifies visual objects with human
users. We use a set of user
interactions with COREF to argue that this objective view of context offers
several compelling
advantages for builders of
collaborative dialogue systems. It enables a coherent, intuitive, and
methodologically workable notion of an agent's uncertainty about what the
current context is. It allows system builders to explore more flexible
reasoning and strategies to manage their agent's uncertainty in interpreting
utterances. And it supports more transparent and data-oriented system-building
techniques.
The third contribution
more closely characterizes the uncertainty that interlocutors face in dialogue
as including numerous tacit events which affect both the current state of their
collaborative activity and the details of how subsequent utterances should be
formulated and interpreted. In particular, domain tasks, such as COREF's object
identification task, exhibit their own idiosyncratic patterns of tacit events
which interlocutors recognize and exploit for efficient communication. We develop a framework by which
dialogue systems can incorporate tacit events into interpretation and thereby
support implicature and accommodation while communicating collaboratively under
uncertainty.
A Common Ground for
Virtual Humans: Using an Ontology in a Natural Language Oriented Virtual Human
Architecture
Arno Hartholt, Research
Programmer, USC
Abstract:
When dealing with large,
distributed systems that use state-of-the-art components, individual components
are usually developed in parallel. As development continues, the decoupling
invariably leads to a mismatch between how these components internally
represent concepts and how they communicate these representations to other
components: representations can get out of synch, contain localized errors, or
become manageable only by a small group of experts for each module. In this
paper, we describe the use of an ontology as part of a complex distributed
virtual human architecture in order to enable better communication between
modules while improving the overall flexibility needed to change or extend the
system. We focus on the natural language understanding capabilities of this
architecture and the relationship between language and concepts within the
entire system in general and the ontology in particular.
Computational Models
of Non-cooperative dialogue
David
Traum, Research Assistant Professor, USC
This talk will outline some cases of
noncooperative
communication
behavior and computational dialogue mechanisms that can
support
these kinds of behavior, including generating, understanding,
and
deciding on strategies of when to engage in uncooperative behavios. Behaviors
of
interest
include
á
unilateral
topic shifts or topic maintenance
á
avoidance
á
competition
á
unhelpful
criticism
á
withholding
of information or services
á
lying
& deception
á
competition
á
antagonism
á
rejection
of empathy
The
decision of whether to be cooperative or not and how to behave in
each
case depends on a number of factors, including the standard
notions
of belief, desire, intention, obligation, and initiative, but
also
factors such as trust, solidarity, power, status, and respect.
We
will present preliminary computational models of these factors and
illustrate
their use with examples of interactions with the characters from the SASO and
TACQ domains.
Day
Two: May 16, 2008
Field
Testing of an Interactive Question-Answering Character
Ron
Artstein, Manager of Corpus Development, USC
Abstract:
We
tested a life-size embodied question-answering character at a convention where
he responded to questions from the audience. The character's responses were
then rated for coherence. The ratings, combined with speech transcripts, speech
recognition results and the character's responses, allowed us to identify where
the character needs to improve, namely in speech recognition and providing
off-topic responses.
Modelling and
Detecting Decisions in Multi-party Human-Human Meetings
Raquel
Fernandez, Stanford University
Abstract:
In an era where almost
anything we do and say is recorded, the demand for automatic methods that
process, understand and summarize information encoded in audio and video
recordings of meetings is rapidly growing. Decision-making discussions
constitute one of the key aspects of meeting interaction. In this talk I will
present our ongoing research on modelling decisions in muti-party meetings and
describe an automatic process to detect decision-making subdialogues. I will
also briefly present recent results on using multimodal information for
addressee detection in small-group meetings.
Tracking
Dragon-Hunters with Language Models
Anton
Leuski, Research Scientist, USC
Abstract:
We are
interested in the problem of understanding the connections between human
activities and the content of textual information generated in regard to those
activities. Firstly, we define and motivate this problem as an important part
in making sense of various life events. Secondly, we introduce the domain of
massive online collaborative environments, specifically online virtual worlds,
where people meet, exchange messages, and perform actions as a rich data source
for such an analysis. Finally, we outline three experimental tasks and show how
statistical language modeling and text clustering techniques may allow us to
explore those connections successfully.
Towards
a formal treatment of corrective feedback
Robin Cooper and Staffan Larsson
University of Gothenburg
In this paper we will present some preliminary work that we have
been conducting on corrective feedback as in the example:
Child: Nice bear.
Adult: Yes, it's a nice panda
The idea is to bring together our previous work on plasticity and
evolution (Larsson 2007), the GF (Ranta 2004, 2007) and TrindiKit/GoDiS
architectures (Larsson 2002, Traum and Larsson 2003) and work on TTR (Cooper
2003, 2006). We will suggest
constructing GF/GoDiS agents in which resources can be updated. We also sketch
a formal account of the semantic plasticity involved in corrective feedback.
References
* GF: http://www.cs.chalmers.se/~aarne/GF/
* TrindiKit: http://www.ling.gu.se/projekt/trindi//trindikit/
* Cooper, Robin (2003): Records and record types in semantic
theory, invited paper, Workshop on Lambda-Calculus, Type Theory, and Natural
Language, King's College London, 8 and 9 December 2003, /Journal of Logic and
Computation/ <http://www3.oup.co.uk/logcom/>,
Vol. 15 No. 2, pp. 99--112.
* Cooper, Robin (2006): Austinian truth, attitudes and type theory
(previous title: Austinian truth in Martin-Lšf type theory), paper presented at
the workshop Barwise and Situation Semantics, Stanford, Cal., 26 June 2003, in
/Research on Language and Computation/ <http://www.dcs.kcl.ac.uk/journals/rolc/>,
Vol. 3 (2005), pp. 333-362, published 2006.
* Staffan Larsson (2002): Issue-based Dialogue Management <http://www.ling.gu.se/%7Esl/Thesis>.
PhD Thesis, Goteborg University.
* Staffan Larsson (2007): Coordinating on ad-hoc semantic systems
in dialogue <http://www.ling.gu.se/%7Esl/Papers/larsson-decalog.pdf>.
In Artstein and Vieu: Proceedings of DECALOG - The 2007 Workshop on the
Semantics and Pragmatics of Dialogue.
* A. Ranta. Grammatical Framework: A Type-Theoretical Grammar
Formalism. /Journal of Functional Programming/, 14(2), pp. 145-189, 2004. Draft
available as ps.gz <http://www.cs.chalmers.se/%7Eaarne/articles/gf-jfp.ps.gz>.
* A. Ranta. Modular Grammar Engineering in GF. /Research on
Language and Computation/, 2007, to appear. Draft available as pdf <http://www.cs.chalmers.se/%7Eaarne/articles/multieng3.pdf>.
* David Traum and Staffan Larsson (2003): The Information State
Approach to Dialogue Management. In Smith and Kuppevelt (eds.): Current and New
Directions in Discourse & Dialogue, Kluwer Academic Publishers.
Culture-Specific
Conversational Behavior
David
Hererra, University of Texas at El Paso
Abstract:
TBA
Virtual
Extras: Multiparty Dialog Simulation for Background Virtual Humans
Dusan
Jan, Graduate Research Assistant, USC
Abstract:
In
this talk I will present our framework for behavior simulation of background
virtual humans involved in multiparty conversation. I will present an overview
of the theories that the framework is built on and describe the three main
components of the framework: conversation algorithm, movement and repositioning
algorithm
and
cultural model. The talk will also cover our current work
on introducing task-based variability to
the simulations and our plan for future improvements.
Unsupervised
Methods for Creating and Evaluating Dialogue Models
Sudeep Gandhe, Graduate
Research Assistant, USC
Virtual humans are being
used in a number of applications, including simulation-based training,
multi-player games, and museum kiosks. Natural language dialogue capabilities
are an essential part of their human-like persona. These dialogue systems have
a goal of being believable and generally have to operate within the bounds of
their restricted domains. Most dialogue systems operate on a dialogue-act level
and require extensive annotation efforts. Semantic annotation and rule
authoring have long been known as bottlenecks for developing dialogue systems
for new domains. In this talk, we investigate several dialogue models for
virtual humans that are trained on an unannotated human-human corpus. These are
inspired by information retrieval and work on the surface text level. We
evaluate these in text-based and spoken interactions and also against the upper
baseline of human-human dialogues.
Evaluating such dialogue
systems is seen as a major challenge within the dialogue research community.
Due to very nature of the task, most of the evaluation methods need substantial
amount of human involvement. Following the tradition in machine translation,
summarization and discourse coherence modeling, we introduce the the idea of
evaluation understudy for dialogue coherence models. Following (Lapata 2006),
we use the information ordering task as a testbed for evaluating dialogue
coherence models. This talk reports findings about the reliability of the
information ordering task as applied to dialogues. We find that simple n-gram
co-occurance statistics similar in spirit to BLEU (Papineni et al. 2001)
correlate very well with human judgments for dialogue coherence.