Conversation as Action Under UncertaintyConversation as Action Under Uncertainty

Tim Paek

Eric Horvitz

AbstractAbstract

Conversation uncertainties of various kinds

Quartet architecture Inference/Decision making under uncertainty 4 levels of analysis Representations Inference procedures Decision strategies

Interaction between a user and dialog system

1. Introduction1. Introduction

Spoken dialog system robust, unified architecture for sharing key uncertainties

Quartet

2. Toward an Architecture for 2. Toward an Architecture for ConversationConversation

General conversation To make themselves understood Uncertainty: communication failure Collaborate/establish mutual belief “feedback” = coordination

• Head nod, “uh huh”

• Clear up uncertainties, take other measures

• Conversation = collaborative effort or joint activity

Grounding 상호 이해를 위해 대화의 presentation 또는 acceptance 를

coordinate 하는 과정 Consideration of how key uncertainties depend on each other and

influence mutual understanding What decisions to make in light of these uncertainties

Quartet Treat grounding as decision making under uncertainty Key uncertainty Bayesian Network Local expected utility/VOI

• Identify action maximize mutual understanding

Focus on handling uncertainties Enable dialog system to adapt strategies Allow components to share uncertainties

2.1 Four Levels of Analysis2.1 Four Levels of Analysis

Evaluate grouding at 4 levels of analysis 4 Levels

Channel level Signal level Intention level: signal 의 semantics 이해 Conversation level

All levels need coordination/collaboration Unified architecture

Model probabilistic dependencies between levels

2.2 Models, Inference, Decisions2.2 Models, Inference, Decisions

atemporal/temporal Bayesian networks compute likelihood of variables of interest Ex) overall grounding status

2.2.1 Modularity2.2.1 Modularity

Maintenance module handle uncertainties about channel and signal levels

Intention module About intention level

Conversation control Keep track of the grounding status Where to focus on resolving uncertainties What grounding actions to take in light of their likely costs/benefits

Reasons for distinct modules Probabilistic dependencies

• abundant with the modules

• sparse between them

Enhancement of the flexibility of Quartet• To be applied to variety of task domains

Belief, decision, degree of detailed necessary for each level varied significantly depending on the communication medium or modality

2.2.2 Representation for Decision Making2.2.2 Representation for Decision Making

Grouding status Diagnoses the overall mutual understanding

2.2.3 Refinement through Value of 2.2.3 Refinement through Value of InformationInformation

Need to refine actions by sharing uncertainties Utterance design

improve understanding

Conversation decision making Capitalize on VOI analysis to ask questions, make

recommendations, and seek out information

VOI analysis• find best evidence in light of the inferred probabilities

Compute VOI 모든 observation 에 대해 expected utility of the best decision 을

계산 VOI recommend a piece of evidence to observe: system 이

recommendation 제공 또는 phrase a question

Exact computation of VOI all possible sequences of observations

Greedy VOI: reasonable approximation

3. Runtime Behavior3. Runtime Behavior

Dialog system ASR NLPWin parser Face-pose tracker

3.1 Providing Services3.1 Providing Services

완전 이해후의 highest expected utility action User 와 requested action 을 연관시키는 것

3.2 Exploiting Multiple Levels3.2 Exploiting Multiple Levels

Goal 이 not so clear at the intention level Consider uncertainties at lower levels of analysis

3.3 Adapting Strategies over Time3.3 Adapting Strategies over Time

Mutual understanding 이 fluctuate adapt strategy over time

Do requested service / resort to only three repair strategies ASK REPEAT, CONFIRM, TROUBLESHOOT (use VOI

analyses to recommend procedures to improve mutual understanding)

4. Conclusions4. Conclusions

Approach to continuous spoken dialog centering on an architecture called Quartet