A preliminary classification of dialogue genres Staffan Larsson Internkonferens 2003.

Slides:



Advertisements
Similar presentations
Technical and design issues in implementation Dr. Mohamed Ally Director and Professor Centre for Distance Education Athabasca University Canada New Zealand.
Advertisements

Technology and teaching A l(IT)eracy perspective.
An information state approach to natural interactive dialogue Staffan Larsson, Robin Cooper Department of linguistics Göteborg University, Sweden.
Negotiative dialogue some definitions and ideas. Negotiation vs. acceptance Clark’s ladder: –1. A attends to B’s utterance –2. A percieves B’s utterance.
OpenDial Framework Svetlana Stoyanchev SDS seminar 3/23.
Using concept mapping to develop a career studies curriculum My objectives in this presentation are to: 1/ Share and explain a career studies concept map.
Dynamic Bayesian Networks (DBNs)
Characteristics of on-line formation courses. Criteria for their pedagogical evaluation Catalina Martínez Mediano, Department of Research Methods and Diagnosis.
Dialogue in Intelligent Tutoring Systems Dialogs on Dialogs Reading Group CMU, November 2002.
Dialogue types GSLT course on dialogue systems spring 2002 Staffan Larsson.
The Role of Software Engineering Brief overview of relationship of SE to managing DSD risks 1.
U1, Speech in the interface:2. Dialogue Management1 Module u1: Speech in the Interface 2: Dialogue Management Jacques Terken HG room 2:40 tel. (247) 5254.
Goteborg University Dialogue Systems Lab Introduction to dialogue systems Staffan Larsson Dialogsystem HT04.
Issues Under Negotiation Staffan Larsson Dept. of linguistics, Göteborg University SigDial, 15/
A Glimpse on Some Dialogue Systems Arthur Chan. Introduction Questions to ponder:  What is a dialogue?  What is a dialogue system?  What are the issues.
What can humans do when faced with ASR errors? Dan Bohus Dialogs on Dialogs Group, October 2003.
Spoken Dialogue Technology How can Jerry Springer contribute to Computer Science Research Projects?
A preliminary classification of dialogue genres or Correlating properties of activities with properties of dialogue systems Staffan Larsson Dept. of linguistics.
Awareness and Distributed Collaboration David Ledo.
Goteborg University Dialogue Systems Lab WP1: GoDiS VCR application Edinburgh TALK meeting 7/
Conversational Agent 1.Two layers: Dialogue manager and Conversational agent. 2.Rule-Based Translator (ELIZA and PARRY) 3. Layer one: Dialogue Manager.
Information, action and negotiation in dialogue systems Staffan Larsson Kings College, Jan 2001.
TrindiKit A toolkit for building and experimenting with dialogue move engines and systems, based on the information state approach.
Issues Under Negotiation Staffan Larsson Dept. of linguistics, Göteborg University NoDaLiDa, May 2001.
01 -1 Lecture 01 Intelligent Agents TopicsTopics –Definition –Agent Model –Agent Technology –Agent Architecture.
Rough schedule Multimodal, multi-party dialogue [30 min] D’Homme, SIRIDUS [10 min] –dialogues with networked devices in a smart house SRI demo (DM), (IBL.
Goteborg University Dialogue Systems Lab GoDiS and TrindiKit MITRE workshop 27/10-03 Staffan Larsson Göteborg University Sweden.
WP1 UGOT demos 2nd year review Saarbrucken Mar 2006.
12 -1 Lecture 12 User Modeling Topics –Basics –Example User Model –Construction of User Models –Updating of User Models –Applications.
1212 Management and Communication of Distributed Conceptual Design Knowledge in the Building and Construction Industry Dr.ir. Jos van Leeuwen Eindhoven.
Call Center – What Really Makes Sense? Call Center – ce este cu adevarat important?
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields Yong-Joong Kim Dept. of Computer Science Yonsei.
ENGLISH LANGUAGE ARTS AND READING K-5 Curriculum Overview.
Beyond Intelligent Interfaces: Exploring, Analyzing, and Creating Success Models of Cooperative Problem Solving Gerhard Fischer & Brent Reeves.
Search Engines and Information Retrieval Chapter 1.
1 A User-Guided Cognitive Agent for Wireless Service Selection in Pervasive Computing George Lee May 5, 2004 G. Lee, P. Faratin, S. Bauer, and J. Wroclawski.
What is STEM? What is STEM?
Dimensions of Human Behavior: Person and Environment
COMPUTER ASSISTED / AIDED LANGUAGE LEARNING (CALL) By: Sugeili Liliana Chan Santos.
Computer Science CPSC 322 Lecture 3 AI Applications 1.
Big Idea 1: The Practice of Science Description A: Scientific inquiry is a multifaceted activity; the processes of science include the formulation of scientifically.
The Information State approach to dialogue modelling Staffan Larsson Dundee, Jan 2001.
Argumentation and Trust: Issues and New Challenges Jamal Bentahar Concordia University (Montreal, Canada) University of Namur, Belgium, June 26, 2007.
An information state approach to natural interactive dialogue Staffan Larsson, Robin Cooper Department of linguistics Göteborg University, Sweden.
From information exchange to negotiation Staffan Larsson Göteborg University
Institute for Collaborative Research in Education, Assessment, and Teaching Environments for STEM Workshop 8: Planning Instruction to Meet the Intent of.
By Elisa S. Baccay. The teacher understands and uses a variety of instructional strategies to encourage students’ development of critical thinking, problem.
Model-Driven Engineering of Behaviors in User Interfaces Efrem Mbaki & Jean Vanderdonckt Université catholique de Louvain (UCL) Louvain School of Management.
Issues in Multiparty Dialogues Ronak Patel. Current Trend  Only two-party case (a person and a Dialog system  Multi party (more than two persons Ex.
L. Ardissono, C. Barbero, A. Goy and G. Petrone Dipartimento di Informatica Universita’ di Torino, Torino, Italy
EFFECTIVE WRITING 8 Readability. Writing - time and resource consuming, stressful process Texts have a strong tendency of using more complex, more sophisticated.
Information state and dialogue management in the TRINDI Dialogue Move Engine Toolkit, Larsson and Traum 2000 D&QA Reading Group, Feb 20 th 2007 Genevieve.
Modeling Speech Acts and Joint Intentions in Modal Markov Logic Henry Kautz University of Washington.
CHAPTER 8 DISCRIMINATIVE CLASSIFIERS HIDDEN MARKOV MODELS.
A Quantitative Trust Model for Negotiating Agents A Quantitative Trust Model for Negotiating Agents Jamal Bentahar, John Jules Ch. Meyer Concordia University.
Chapter 1. Cognitive Systems Introduction in Cognitive Systems, Christensen et al. Course: Robots Learning from Humans Park, Sae-Rom Lee, Woo-Jin Statistical.
1/14/ :59 PM1/14/ :59 PM1/14/ :59 PM Research overview Koen Victor, 12/2007.
Goteborg University Dialogue Systems Lab Comments on ”A Framework for Dialogue Act Specification” 4th Workshop on Multimodal Semantic Representation January.
Artificial Intelligence: Research and Collaborative Possibilities a presentation by: Dr. Ernest L. McDuffie, Assistant Professor Department of Computer.
Tutorials and Quick Guides A quick introduction. Overview  Genre of Tutorial  Genre of Quick Guide  Genre of Reference  Genre of User Manual  Attributes.
Agent-Based Dialogue Management Discourse & Dialogue CMSC November 10, 2006.
Inquiry Primer Version 1.0 Part 4: Scientific Inquiry.
Data Resource Management – MGMT An overview of where we are right now SQL Developer OLAP CUBE 1 Sales Cube Data Warehouse Denormalized Historical.
PSYC 206 Lifespan Development Bilge Yagmurlu.
“Intelligent User Interfaces” by Hefley and Murray A 1993 Perspective
Next Step #2: Acquisition Dialogue
Thrust IC: Action Selection in Joint-Human-Robot Teams
Associative Query Answering via Query Feature Similarity
Attentive User Interfaces
Presentation transcript:

A preliminary classification of dialogue genres Staffan Larsson Internkonferens 2003

overview previous typologies –Dahlbäck 1997 –Allen dimensions of classification –moves and infostate –dialogue features –activity features Allwood’s activity based pragmatics

Goal –A classification of dialogue genres –Relevant for development of dialogue systems –Dimensions of classification correlating with dialogue system properties We will try to correlate our classification with GoDiS information state etc.

Dahlbäck (1997) modality: spoken/written kinds of agents: human/computer interaction: dialogue/monologue context: spatial, temporal number & type of tasks –simultaneous? dialogue-task distance –similarity of dialogue structure – task structure kinds of shared knowledge exploited –perceptual, linguistic, cultural

Allen et. al. (2001) technique used example tasktask complexity dialogue phenomena handled finite-state script long-distance dialing least complex user answers questions frame-basedgetting train timetable info user asks questions, simple clarifications by system sets of contexts travel booking agent shifts between predetermined topics plan-based models kitchen design consultant dynamically generated topic structures, collaborative negotiation subdialogues agent-based models disaster relief management most complex different modalities (e.g. planned world and actual world)

discussion Dahlbäck: several dimensions, but not so relevant for our purpouses Allen: single dimension of classification some types of dialogue not included –tutorial –explanatory –instructional We want a classification –based on several independent dimensions –covering not only information seeking and collaborative planning dialogue

Basic distinction: inquiry vs. action-oriented dialogue IOD: raising and addressing issues AOD introduces (non-communicative) actions to performed (requests) pure AOD vs. AOD+IOD dialogue type movesInfostate components inquiry- oriented ask answer/assert QUD ISSUES action- oriented request confirm ACTIONS

General dialogue phenomena grounding & accommodation probably present in all H-H dialogue; not included in classification negotiation perhaps less frequent featureMovesinfostate components groundingICM movesTMP, grounding issues accommodationaccommodateX (tacit moves) - negotiationpropose QuestionSet(Answer)

activity-related factors result type: (what goes in SH.COM and SH.ACTIONS) –simple: proposition, action –complex: plan, proof, explanation requires incremental construction proactivity of external process –passive: database, simple device –(pro)active: device, e.g. Robot –this dimension correlates with the way the system is connexted to the device distribution of decision rights –disjoint: each question can be answered only by one DP (e.g. destination city, price); this DP ”decides” the answer –shared: some question(s) should be answered jointly; negotiation may be needed –so this dimension correlates with negotiation

activity type / application dialog type result typeexternal process decision rights database searchIODsimple: price etc. complex: itinerary passive (database) disjoint ticket bookingAOD+ IOD simple: flightpassive (database) disjoint simple device control AOD+ IOD simple: actionspassive or active disjoint instructional (sys instructs usr) AOD+ IOD simple: actionspassive (manual) disjoint offline planning, incl. itinerary planning, complex device control AODcomplex: plan(s)passive (planner) shared online planning, e.g. TRIPS AOD+ IOD complex: planactive (device) shared explanationIODcomplex: proof or explanation passive (inference engine) shared tutorialIOD/ AOD complex?passive (planner) disjoint narrationIODcomplex: narrativepassivedisjoint

Possible additional activity- related factors static/dynamic ext. Process –Correlates with ability to apply updates to resource [is this interesting?] distribution of information –Symmetric: DPs have same kind of information –Asymmetric: DPs have different kinds of information –Correlates with what? Rules for who should answer which questions? …?

Allwood’s activity-based pragmatics Levels of activity/context –Physical: artifacts etc. –Biological –Psychological: beliefs, desires, intentions, … –Social: incl. rights & obligations, communicative and task- related How do these fit with the proposed activity-related factors? –Distribution of decision rights: social –Proactivity of external process: Physical (Biological? Psychological?) –Result type: Psychological? –Information state components: Psychological and social

comments The presence of grounding and accommodation may be independent of activity –… but not their form Make a decision graph which based on activity leads to dialogue genre/properties of system –System properties should be given nonformal but exact formulations that can be used by nonexperts –Correlation to system properties given in table form; correlate with libraries?

More thoughts Table shows –A classification of activities according to features of a dialogue system needed to particitpate in dialogues in these activities –Very specific activity types; e.g. Dialogue with Panasonic VCR 4500? Which level is right? Rule libraries come with infostate extensions/requirements, and with additional moves –Requirements not only on structure, but also on how it’s to be used, e.g. What does the order of a queue mean?

more How feedback is realised –Have different ICM grammars for different kinds of activity –Which factors determine genre-specific ICM? Written/spoken Noisiness Available modalities How important to be right? AOD->higher requirements on recognition, more checks? Negotiation (in ”alternatives” sense) not really directly correlated with shared decision rights

More… Possible additional dimensions –Opposing goals? –Argumentation? –Number of simultaneous tasks (one or several) –Several instances of same task-type simultaneously? How handle classroom questions?