Feedback Request Timing Based on User Sentiment
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Solution Overview
Problem
Speech recognition systems face challenges in requesting feedback from users at optimal times to ensure accuracy and unbiased responses, as existing systems often overwhelm users with requests, leading to biased feedback due to emotional states or environmental factors.
Innovation Solution
Implementing a system that determines the appropriateness of requesting feedback based on implicit signals such as sentiment, tone of voice, and context, using pre-established feedback prompts and dynamic configuration to ensure user receptiveness, and balancing user experience with feedback integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If feedback requests are frequently sent to users, then the system can gather more feedback data, but users become overwhelmed and frustrated leading to biased feedback
Solution Approach 1:
The system performs preliminary analysis of implicit signals (sentiment, tone, context) before sending feedback requests to determine if the user is in a suitable state to provide unbiased feedback, preventing premature or inappropriate requests that would compromise feedback quality
Solution Approach 2:
The system uses feedback loops to monitor user responses and adjust future feedback request timing based on observed user states and feedback patterns, optimizing the balance between data collection volume and feedback quality over time
2Productivity
If feedback is requested during all interactions, then more feedback opportunities are captured, but user experience deteriorates due to excessive requests
Solution Approach 1:
The system applies partial action by selectively requesting feedback only in specific situations where implicit signals indicate the user is receptive, rather than excessively requesting feedback in all interactions, thus maintaining user experience while still collecting sufficient feedback data
Solution Approach 2:
The system implements periodic feedback requests based on timing analysis of user interactions and states, spacing requests appropriately rather than continuously, which maintains productivity while respecting user experience
3Device complexity
If the system requests feedback without analyzing user state, then feedback requests are simple to implement, but feedback accuracy decreases due to emotional bias
Solution Approach 1:
The system performs preliminary analysis of implicit signals including sentiment, tone of voice, and context before determining whether to request feedback, ensuring users are in an appropriate state to provide accurate, unbiased feedback
Solution Approach 2:
The system introduces an intermediary analysis layer that evaluates implicit signals as a mediator between the user and the feedback request mechanism, filtering out requests that would likely yield biased feedback while maintaining simple overall system architecture
Data Source
AI summary
Techniques for selectively requesting feedback from users are described. A system may receive a user input and perform an action responsive to the user input. The system may determine whether feedback should be requested from the user. Such determination may be based on various signals such as the user's present emotional state, whether the user input included profanity, whether the user input interrupted an output of the system, etc. When the system determines feedback should be requested, the system may select a feedback prompt pre-established by a domain, skill, or the like. After the system outputs the response to the user input, the system may output the feedback prompt.