Digital Assistant Confirmation Prompts for Intent Accuracy
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Solution Overview
Problem
Existing digital assistants lack the ability to identify situations where user confirmation is necessary when generating voice or text data based on user utterances, leading to potential misinterpretation or mismatch in user intent.
Innovation Solution
An electronic device equipped with a communication module, processor, and memory, which includes a method to generate and output notifications requesting user confirmation when generating voice or text data using a digital assistant, based on characteristics of user utterances and data received from another device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the digital assistant automatically generates voice or text data based on user utterances, then the responsiveness and automation of the system is improved, but the accuracy and reliability of user intent interpretation deteriorates
Solution Approach 1:
The system introduces a confirmation feedback mechanism where generated responses are presented to the user for approval before being sent. This feedback loop allows the user to verify the accuracy of the digital assistant's interpretation and correct any misunderstandings, thereby resolving the contradiction between automation and reliability.
Solution Approach 2:
The system performs preliminary analysis of the generated response against the original user utterance characteristics before final transmission. By pre-checking the alignment between user intent and generated response, the system ensures higher accuracy while maintaining automation, thus resolving the contradiction between speed and reliability.
2Productivity
If the digital assistant generates responses without user confirmation, then the productivity and response speed are improved, but the loss of information regarding user intent deteriorates
Solution Approach 1:
The confirmation request mechanism serves as a feedback channel that prevents information loss by ensuring the generated response accurately reflects user intent before transmission. This selective confirmation approach maintains productivity while preventing information loss in critical cases.
Solution Approach 2:
The system dynamically adjusts the confirmation threshold based on various parameters such as the clarity of user intent, the type of action being performed, and the confidence level of the generated response. This parameter-based adjustment optimizes the balance between response speed and information accuracy.
3Reliability
If the system requests user confirmation for all generated responses, then the reliability of user intent interpretation is improved, but the device complexity and operational overhead increase
Solution Approach 1:
The system applies confirmation requests selectively rather than uniformly to all responses. Confirmation is triggered only in specific local conditions such as when the generated response deviates from expected patterns, when the confidence level is below a threshold, or when the action has significant consequences. This localized approach maintains reliability while reducing overall system complexity.
Solution Approach 2:
The system implements partial confirmation by requesting user approval only for specific types of responses that require higher accuracy, rather than all responses. This partial action approach maintains reliability for critical operations while minimizing the operational overhead and complexity of the confirmation system.
Data Source
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AI summary
Disclosed is an electronic device. The electronic device may execute an application for transmitting and receiving at least one of text data or voice data with another electronic device using the communication module, in response to occurrence of at least one event, based on receiving at least one of text data or voice data from the another electronic device, identify that a confirmation is necessary using the digital assistant based on at least one of text data or voice data being generated based on a characteristic of ab utterance using a digital assistant, generate a notification to request confirmation using the digital assistant based on confirmation being necessary, and output the notification using the application. A method for identifying that a confirmation is necessary may include identifying using voice data or text data that is received from another electronic device using a rule-based or AI algorithm. When a confirmation is necessary is identified using the AI algorithm, the method may use machine learning, neural network, or a deep learning algorithm.