Towards a Method For Evaluating Naturalness in Conversational Dialog Systems Victor Hung, Miguel Elvir, Avelino Gonzalez & Ronald DeMara Intelligent Systems Laboratory University of Central Florida IEEE International Conference on Systems, Man, and Cybernetics San Antonio, Texas October 12, 2009

University of Central Floridawww.ucf.edu Agenda  Introduction  Background  Approach  Project LifeLike

University of Central Floridawww.ucf.edu Introduction  Interactive Conversation Agent Evaluation  Cannot rely solely on quantitative methods  Subjectivity in ‘naturalness’  No general method to judge how well a conversation agent performs  Pivotal focus will be defining naturalness  How well a chatbot can maintain a natural conversation flow  LifeLike virtual avatar project as a backdrop  Provide a suitable validation and verification method

University of Central Floridawww.ucf.edu Background: Early Systems  Declarative knowledge to process data  Explicitly defined rules  Constrained knowledge  Limited capacity to assess and adapt  Goal-oriented and data-driven behavior  ALICEbot

University of Central Floridawww.ucf.edu Background: Naturalness  Automatic Speech Recognition  Context retrieval experimentation  Intelligent tutoring  Adaptive Control of Thought  Knowledge Acquisition agents  Quality of the information received  Conversation length metric  ALICE-based bots

University of Central Floridawww.ucf.edu Background: Recent Advances  Sentence-based template matching  Simple conversational memory  CMU’s Julia, Extempo’s Erin  Interaction occurs in a reactive manner  Wlodzislaw et al  Development of cognitive modules and human interface realism  Ontologies, concept description vectors, semantic memory models, CYC

University of Central Floridawww.ucf.edu Background: Recent Advances  Becker and Wachsmuth  Representation and actuation of coherent emotional states  Lars et al  Model for sustainable conversation  Awareness of the human users and the conversation topics  Relies on textual input similar to ELIZA  Use of natural language processing for reasoning about human speech

University of Central Floridawww.ucf.edu Background: Conclusion  Breadth of research using chatbots  Focus on creating more sophisticated interpretative conversational modules  Need exists for generalizable metrics  Conversational agents widely experimented with, but it has been lacking a basic framework for universal performance comparison

University of Central Floridawww.ucf.edu Approach: Previous Approaches  Mix of quantitative and qualitative measures  Subjective matters employ human user questionnaire  Semeraro et al’s bookstore chatbot  7 characteristics: impression, command, effectiveness, navigability, ability to learn, ability to aid, comprehension.  Does not provide statistical conclusiveness  General indicator of performance

University of Central Floridawww.ucf.edu Approach: Previous Approaches  Shawar and Atwell’s universal chatbot evaluation system  ALICE-based Afrikaans conversation agent  Dialog efficiency  Dialog quality: reasonable, weird but understandable, and nonsensical  Users’ satisfaction, qualitatively measured  Proper assessment is end result in how successfully it accomplishes its intended goals

University of Central Floridawww.ucf.edu Approach: Previous Approaches  Evaluation of naturalness similar to general chatbot assessment  Rzepka et al’s 1-to-10 scale metrics  Naturalness degree  Willing to continue a conversation degree  Human judges used these measures to evaluate a conversation agent’s utterances  No concrete baseline for naturalness  Able to make relative measurements of naturalness between dialog agents

University of Central Floridawww.ucf.edu Approach: Chatbot Objectives  Walker et al’s PARAdigm for DIalogue System Evaluation (PARADISE)  Dialog performance relates to the experience of the interaction (means)  Task success is concerned with the utility of the dialog exchange (ends)  Objectives  Better than other dialog system solutions  Similar to a human-to-human (naturalness) interaction

University of Central Floridawww.ucf.edu Approach: Task Success  Measure of goal satisfaction  Attribute-value matrix  Derived from PARADISE  Expected vs. actual  Task success (κ) computed as the percentage of correct responses

University of Central Floridawww.ucf.edu Approach: Performance Function  Derived from PARADISE  Total effectiveness  Task success (κ) weighted by (α)  Dialog costs (c i ) weighted by (w i )  Function (N) uses Z-score normalization  Balance out (κ) and (c i )

University of Central Floridawww.ucf.edu Approach: Proposed System  Task success  Dialog costs  Efficiency  Resource consumption  Quantitative  Quality  Actual conversational content  Quantitative or qualitative

University of Central Floridawww.ucf.edu Questions