Dynamic Dialogue Script Adaptation for Social Robots
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Solution Overview
Problem
Social robots face challenges in adapting interactions with humans effectively, as they lack personalized and dynamic dialogue scripts, leading to suboptimal engagement and user experience.
Innovation Solution
A data management system that analyzes interaction log data from one social robot to create an interaction content database, which is then used by another social robot to adapt its interactions with humans, associating specific content with user reactions and profiles to enhance engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If social robots use fixed dialogue scripts, then device complexity is reduced, but adaptability to different users and situations deteriorates
Solution Approach 1:
The patent implements dynamic dialogue scripts that automatically adapt to user characteristics and interaction context. The system transitions from static pre-programmed dialogues to dynamic scripts that are generated and modified in real-time based on user profiles, interaction history, and feedback, thereby resolving the contradiction between simplicity and adaptability
Solution Approach 2:
The system incorporates feedback mechanisms where user reactions to dialogue content are collected and used to continuously refine and personalize interaction scripts. This feedback loop enables the robot to learn from interactions and improve its dialogue adaptability without requiring complex manual reprogramming
2Reliability
If social robots collect and analyze interaction data from multiple sources, then interaction quality improves, but data management complexity increases
Solution Approach 1:
The patent introduces a centralized data management system that acts as an intermediary between multiple social robots and the cloud infrastructure. This intermediary handles data collection, normalization, storage, and distribution, thereby improving interaction quality through comprehensive data analysis while shielding individual robots from the complexity of managing disparate data sources
Solution Approach 2:
The data management system is designed as a universal platform that serves multiple functions: collecting interaction logs from various robots, analyzing user feedback, generating personalized dialogue scripts, and distributing updated scripts back to robots. This multi-functional approach consolidates complexity into a single system rather than requiring each robot to handle all data management tasks independently
3Productivity
If interaction content is continuously updated based on user feedback, then user engagement improves, but information consistency challenges arise
Solution Approach 1:
The system performs preliminary actions by pre-processing and normalizing interaction data before storage, and by pre-generating dialogue script templates based on analyzed user profiles. This preliminary organization of information ensures that when content is updated in real-time, consistency is maintained through the structured framework established in advance
Solution Approach 2:
The patent uses copying mechanisms where validated dialogue patterns and user profile information are replicated across multiple interaction instances. Once a successful interaction pattern is identified through feedback analysis, it is copied and adapted for similar situations, ensuring information consistency while still allowing for personalized engagement
Data Source
AI summary
A system and methods for incorporating disparate sources of collective feedback in the preparation and execution of an initial interaction between a social robot and a human being is disclosed. These methods include retrieving interaction content, assigning a life cycle to new content, detecting and removing expired life cycle content, modifying interaction scripts to include new interaction content and sending the modified interaction script to at least one social robot, wherein the at least one social robot executes the modified script during the period of time specified by the life cycle associated with the interaction topic to obtain an improved interaction with a human receiving, by the data management system, interaction log data.