Audio Sensor Selection for Audience Metering
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Solution Overview
Problem
Traditional audience measurement systems face challenges in accurately selecting the optimal audio sensors for media monitoring, particularly when dealing with varying speaker configurations and acoustic environments, which can lead to suboptimal recognition of media watermarks.
Innovation Solution
The system employs a selection mechanism that identifies and selects the appropriate audio sensors based on the speaker configuration and acoustic environment, using a combination of front-facing, rear-facing, and surround sound configurations to optimize watermark recognition, and periodically updates the sensor configuration to adapt to changes in the media presentation setup.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed audio sensor configuration is used, then the device complexity is reduced, but the measurement precision deteriorates due to inability to adapt to varying speaker configurations and acoustic environments
Solution Approach 1:
The patent implements dynamic audio sensor configuration that automatically adapts to different speaker configurations and acoustic environments. The system periodically tests different sensor configurations and selects the optimal one based on watermark recognition performance, transforming a static sensor setup into a dynamic, adaptive system that maintains high measurement precision across varying conditions
Solution Approach 2:
The system performs self-configuration by automatically testing different audio sensor configurations and selecting the optimal setup without requiring manual intervention. The meter autonomously monitors watermark recognition quality metrics and adjusts sensor selection accordingly, enabling the device to self-optimize its performance in different acoustic environments
2Reliability
If multiple audio sensor configurations are tested and selected, then the reliability of media identification is improved, but the loss of time increases due to periodic configuration updates and testing
Solution Approach 1:
The system implements periodic testing of audio sensor configurations at scheduled intervals rather than continuously. This approach maintains reliable media identification by regularly updating sensor selection while minimizing time loss through间断性 (intermittent) testing rather than continuous evaluation, balancing reliability with time efficiency
Solution Approach 2:
The system uses feedback from watermark recognition quality metrics to determine when configuration updates are necessary. By monitoring recognition quality and triggering updates only when performance degrades or at scheduled intervals, the system maintains high reliability while avoiding unnecessary testing and updates that would consume time
Data Source
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AI summary
Methods, apparatus, systems and articles of manufacture to perform audio sensor selection in an audience metering device (114) are disclosed. An example method includes identifying (1220) a first configuration and a second configuration, the first and second configurations to identify respective gain values to be applied to at least one of a first signal output by a first audio sensor of the audience metering device (114) and a second signal output by a second audio sensor of the audience metering device; obtaining (1240) a first quality metric associated with a first media identification when the gain values of the first configuration are applied; obtaining (1240) a second quality metric associated with a second media identification when the gain values of the second configuration are applied; selecting (1270) one of the first configuration or the second configuration based on a comparison of the first quality metric and the second quality metric; and identifying media based on the first signal and the second signal with the selected one of the configurations applied.