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Strategic Talk in Film.
Sabine Payr1, Marcin Skowron1, Anna Dobrosovestnova1
1Austrian Research Institute for Artificial Intelligence OFAI, Vienna/Austria.
Cybernetics and Systems
|January 30, 2018
Summary
This study models strategic talk for conversational agents in long-term coaching roles. It analyzes film mentor dialogues to understand how agents can effectively change user attitudes and goals over time.
Area of Science:
- Artificial Intelligence
- Human-Computer Interaction
- Computational Linguistics
Background:
- Conversational agents are increasingly used for long-term educational and persuasive tasks like health coaching.
- Effective long-term interaction requires agents to possess complex strategic goals and adaptable communication strategies.
- Strategic talk, defined as conversation aimed at altering attitudes or goals, is crucial for these agents.
Purpose of the Study:
- To develop a model for strategic talk applicable to conversational agents.
- To analyze mentor-like communication strategies in extended dialogues.
- To provide insights into agent behavior for persuasive and educational applications.
Main Methods:
- Analysis of a corpus of film mentor utterances.
- Annotation of dialogue data based on a developed model of strategic talk.
- Interpretation of annotated data to identify realization and sequencing of mentor strategies.
Main Results:
- Identified key strategies employed by mentor characters in film dialogues.
- Demonstrated that strategic talk can span multiple conversational segments over extended periods.
- Provided a framework for understanding the sequential nature of persuasive communication.
Conclusions:
- A robust model of strategic talk is essential for long-term conversational agent effectiveness.
- Insights from mentor behavior can inform the design of more sophisticated persuasive agents.
- Further research can refine agent capabilities in strategic goal management and interaction.
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