In-Vehicle Passenger Perception Detection via Conversation Analysis
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Solution Overview
Problem
Current methods fail to reliably monitor and assess passenger perception of informational content, such as advertising, within vehicles, which is crucial for advertisers to gauge the effectiveness of their content.
Innovation Solution
A method and device that record conversations inside a vehicle using a microphone and analyze them to detect if informational content has been perceived by passengers, utilizing conversation analysis and recognition data to infer perception, with the ability to distinguish between general conversations and content-related discussions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If advertising content is output in the vehicle, then the advertising company can reach passengers, but it cannot determine whether the advertising has been perceived by passengers
Solution Approach 1:
The patent uses conversation analysis as an intermediary method to indirectly detect advertising perception. Instead of directly measuring whether passengers perceived the advertising, the system analyzes conversations to find references to advertising content, using the conversation as a mediator between the advertising output and perception detection.
Solution Approach 2:
The system establishes a feedback loop where advertising content is output, conversations are recorded and analyzed, and the results feed back to determine whether the advertising was perceived. This closed-loop feedback mechanism enables continuous optimization of advertising delivery based on actual passenger perception.
2Measurement precision
If conversation analysis is performed to detect advertising perception, then reliable detection is achieved, but processing time and computational resources increase
Solution Approach 1:
The system applies partial action by focusing conversation analysis only on time intervals when advertising is actually output or shortly after. Instead of continuously analyzing all conversations, the system selectively analyzes relevant time windows, reducing overall processing time while maintaining detection accuracy for advertising-related content.
Solution Approach 2:
The system performs preliminary action by pre-processing and storing conversation data during advertising output intervals, so that analysis can be efficiently conducted later. Conversations are recorded and prepared in advance, allowing for faster subsequent analysis without compromising detection precision.
3Reliability
If continuous conversation monitoring is implemented, then passenger perception can be detected, but privacy concerns and data protection issues arise
Solution Approach 1:
The system extracts only the necessary information for advertising perception detection from conversations, separating this from other personal data. By taking out only the specific elements needed to determine whether advertising was perceived (such as keywords related to ad content), the system minimizes privacy intrusion while maintaining monitoring reliability.
Solution Approach 2:
The system converts the potential harm of continuous monitoring into a benefit by using automated conversation analysis that actually reduces the need for intrusive continuous surveillance. The analysis of recorded conversations provides reliable perception data without requiring active, continuous monitoring that would be more privacy-intrusive.
Data Source
AI summary
The invention relates to a method for monitoring a passenger of a vehicle in which it is detected if informational content perceptible in the vehicle is being output, and recognition data on output informational contents are recorded. The method provides that a conversation in the interior of the vehicle is recorded using a microphone in the interior of the vehicle, at least during or for a time interval after the outputting of the informational content, an analysis is performed of the recorded conversation that was held while or for a time interval after the informational content was output, and by using the conversation analysis and the recorded recognition data of the informational content output during or before the conversation, it is detected whether the output informational content was perceived by a passenger of the vehicle.