Action Processing with Group-State Vectors for Nonverbal Evaluation
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Solution Overview
Problem
Existing evaluation methods for nonverbal communication skills in interpersonal interactions, such as counseling, are inadequate, particularly in early stages of rapport building, leading to insufficient intervention support.
Innovation Solution
An action processing device that evaluates nonverbal communication using a knowledge database to associate sensing information with vector information, allowing for a more comprehensive assessment of group communication states and generating intervention actions based on these evaluations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If evaluation methods focus on verbal response techniques, then it is easy to clearly state and provide examples of what should be said, but the evaluation of nonverbal response techniques becomes insufficient
Solution Approach 1:
The evaluation system segments communication evaluation into multiple independent components: verbal response evaluation and nonverbal response evaluation. Each component is assessed separately using different methodologies, allowing comprehensive evaluation without compromising the accuracy of nonverbal technique assessment while maintaining the ease of providing verbal examples.
Solution Approach 2:
The system introduces an intermediary AI model that analyzes sensing information (such as video, audio, or sensor data) to evaluate nonverbal response techniques. This intermediary processes raw sensing data and converts it into evaluable metrics, enabling accurate nonverbal evaluation without requiring direct human observation and interpretation.
2Measurement precision
If evaluation relies on sensing information in early counseling stages, then nonverbal response techniques can be assessed, but the client's response may not reflect actual thoughts when rapport is immature
Solution Approach 1:
The system performs preliminary evaluation of communication quality and rapport status before fully interpreting client responses. By assessing the maturity of the counselor-client relationship in advance, the system can determine whether sensing information reliably reflects actual client thoughts, adjusting evaluation criteria accordingly to maintain accuracy.
Solution Approach 2:
The evaluation system dynamically adjusts its interpretation criteria based on the current rapport level between counselor and client. When rapport is immature, the system applies different evaluation standards compared to when rapport is established, allowing accurate interpretation of nonverbal responses at each stage of the counseling relationship development.
3Measurement precision
If comprehensive sensing information is collected for evaluation, then nonverbal communication can be assessed, but the complexity of the evaluation system increases
Solution Approach 1:
The system extracts only the essential features and indicators needed for nonverbal communication evaluation from comprehensive sensing information. Rather than processing all available data, it identifies and focuses on key parameters such as facial expressions, body language, tone of voice, and posture, simplifying the evaluation process while maintaining comprehensiveness.
Solution Approach 2:
The system transforms complex sensing information into standardized evaluation parameters with defined weightings and thresholds. By converting raw sensor data into normalized metrics with clear interpretation criteria, the system maintains comprehensive evaluation capability while reducing computational and operational complexity.
Data Source
AI summary
To perform more appropriate evaluation on an action related to communication.An action processing device 1 for evaluating an action related to communication of a group of action subjects performing the communication with each other includes a group state index calculation unit 104 configured to calculate, based on second sensing information of a second group to be evaluated, a second group state index related to a state of communication in the second group, a vector information generation unit 105 configured to generate visible information based on the second group state index and to generate second vector information by vectorizing the visible information, and an action evaluation unit configured to evaluate the action of the second group based on a first group state index associated with a piece of first vector information whose comparison result with the second vector information satisfies a predetermined condition among pieces of first vector information serving as a reference of the knowledge database.