Emotional State Analysis for Message Response Suggestion
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Solution Overview
Problem
Current technologies lack an effective method to determine and suggest appropriate responses to incoming messages based on the emotional state of the message sender, leading to inadequate emotional engagement in communication.
Innovation Solution
A method and apparatus that analyze incoming messages to determine the emotional state of the sender, identify a target emotional state, and suggest responses by searching historical messages and user characteristics, using multivariate search techniques and emotional response databases to provide relevant and contextually appropriate responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If emotional state analysis and historical message search are implemented, then emotional engagement and response relevance are improved, but device complexity and processing time increase
Solution Approach 1:
The system segments the response generation process into distinct modules: emotional state analysis module, historical message search module, and response selection module. Each module handles a specific aspect of the task, making the overall complex system manageable and maintainable while achieving high response relevance through coordinated operation of these specialized components.
Solution Approach 2:
The patent introduces an intermediary processing layer that analyzes emotional states and mediates between incoming messages and historical message databases. This intermediary layer (comprising emotion detection algorithms and search coordination mechanisms) bridges the gap between raw message data and meaningful response selection, improving reliability while managing complexity through specialized intermediate processing.
2Reliability
If emotional state analysis and historical message search are implemented, then emotional engagement and response relevance are improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-analyzing and categorizing historical messages during off-peak times, organizing them by emotional context and relevance. Emotional state analysis frameworks are pre-loaded and ready for rapid deployment. This preliminary preparation significantly reduces the actual processing time required when generating responses to incoming messages, as the heavy lifting of analysis has already been done in advance.
Solution Approach 2:
The patent implements dynamic processing that adjusts the depth and scope of emotional state analysis and historical message search based on real-time conditions such as message urgency, user preferences, and system load. When time is critical, the system dynamically reduces the search scope or uses simplified emotion detection, while maintaining high response relevance through intelligent adaptation of processing intensity to match situational requirements.
Data Source
AI summary
Systems, networked devices, and methods are disclosed for suggesting a response to an incoming message. In one aspect, a method includes receiving, by a first electronic device for a first user, the incoming message from a second user, determining a present emotional state of the second user based on the incoming message, determining a target state of the second user based on the present emotional state, determining a response to the incoming message based on the target state, and writing data derived from the response to an output device. In some aspects, the method also includes identifying other users having characteristics similar to those of the second user, and selecting the response to the incoming message from responses provided to users having the similar characteristics.