Affective Interaction System Emotion Recognition Architecture
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional human-computer interaction systems neglect emotional aspects, leading to unsatisfactory user experiences as they fail to recognize and respond to human emotions, which are integral to communication.
Innovation Solution
An affective interaction system and method that includes an affective interaction computing module with a user intention computing processor to identify emotions and formulate responses in various modalities, enabling empathetic interactions by collecting, recognizing, and generating emotional expressions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional human-computer interaction systems are used, then the system structure remains simple, but the user experience deteriorates due to lack of emotional recognition and response
Solution Approach 1:
The affective interaction system is divided into distinct functional modules: emotion recognizer module that processes emotional expressions, user intention computing module that determines interaction and affective intentions, and strategy formulator module that generates appropriate responses. This segmentation allows each module to specialize in specific tasks, improving overall system reliability for emotional interaction while managing complexity through modular design.
Solution Approach 2:
The system integrates multiple functions into a unified affective interaction framework that simultaneously handles emotion recognition, intention identification, and response generation. The user intention computing processor performs both interaction intention recognition and affective intention determination, making the system multi-functional and improving user experience without requiring entirely separate systems.
2Reliability
If emotion recognition and response generation are added to the system, then user experience improves, but the computing complexity increases
Solution Approach 1:
The computing module is segmented into specialized sub-modules: emotion recognizer for processing emotional expressions, user intention computing processor for determining intentions, and strategy formulator for generating responses. Each segment handles specific computational tasks, improving affective interaction accuracy while managing computing complexity through functional decomposition.
Solution Approach 2:
The system employs feedback mechanisms where the emotion recognizer continuously monitors user emotional states and feeds this information back to the user intention computing processor and strategy formulator. This feedback loop enables adaptive response generation that improves affective interaction accuracy by adjusting to real-time emotional cues without requiring overly complex pre-computation.
3Measurement precision
If the system collects and processes multiple types of emotion-related data, then the accuracy of emotion recognition improves, but the data processing complexity increases
Solution Approach 1:
The data processing is segmented into multiple parallel streams: one for collecting emotion-related data from various sources, another for recognizing and classifying emotional expressions, and a third for determining user intentions. This segmentation allows the system to process multiple data types simultaneously, improving emotion recognition accuracy while managing complexity through parallel processing architecture.
Solution Approach 2:
The emotion recognizer and user intention computing processor are designed as multi-functional modules that can handle various types of emotion-related data including facial expressions, voice tone, text input, and physiological signals. This universality allows the system to process diverse data sources through unified processing pipelines, improving measurement precision without proportionally increasing data processing complexity.
Data Source
AI summary
The present disclosure includes an affective interaction apparatus, comprising an affective interaction computing module including a user intention computing processor to receive emotion-related data and an emotion state of a user; and identify a user intention based on the emotion-related data and the emotion state, the user intention including an affective intention and/or an interaction intention, the affective intention corresponding to the emotion state and including an affective need of the emotion state, the interaction intention including one or more transaction intentions.