Media Crediting via Frequency Peak Detection
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Solution Overview
Problem
Existing media monitoring systems face inaccuracies in crediting media exposure due to changes in presentation rates, such as speeding up or slowing down of media assets, leading to false negatives where altered rates result in incorrect identification of media assets.
Innovation Solution
The system generates a frequency spectrum of audio data to detect peaks in specific frequency ranges, determining the presentation rate by comparing the magnitudes of these peaks and adjusting signature matching algorithms to accurately credit media exposure based on whether the presentation rate is original or altered.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If audio signatures are generated from media signals to identify media assets, then media identification can be performed, but inaccuracies occur when presentation rates are altered (speeding up or slowing down)
Solution Approach 1:
The system changes the parameter of presentation rate by detecting peaks in the frequency spectrum at different time intervals. By monitoring how the time between peaks changes, the system can identify whether the media is being presented at an altered rate, and adjust the audio signature generation accordingly to maintain accurate identification despite rate changes.
2Reliability
If media monitoring systems use fixed signature matching algorithms, then processing is simple, but false negatives occur when presentation rates are altered
Solution Approach 1:
The system transitions from a static signature matching algorithm to a dynamic one that adapts to presentation rate changes. The algorithm continuously monitors the time between frequency spectrum peaks and adjusts the audio signature generation and matching process in real-time, ensuring reliable crediting while handling variable presentation rates.
Solution Approach 2:
The system implements feedback by monitoring the time between frequency peaks and using this information to adjust the audio signature matching process. This feedback loop allows the system to detect presentation rate alterations and modify its behavior accordingly, preventing false negatives while maintaining processing efficiency.
3Measurement precision
If the system monitors frequency spectrum peaks to detect presentation rate changes, then accurate crediting is achieved, but processing time increases
Solution Approach 1:
The system applies partial action by focusing the frequency spectrum analysis on specific peak detection rather than processing the entire spectrum in detail. By identifying key peaks and measuring the time between them, the system achieves accurate presentation rate detection without the computational burden of comprehensive spectral analysis, thus reducing processing time.
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture are disclosed to credit media based on the presentation rate. An example apparatus disclosed herein includes memory and instructions. The example apparatus disclosed herein further includes at least one processor to execute the instructions to cause the at least one processor to at least detect a first peak in a first frequency range of audio data associated with monitored media, detect a second peak in a second frequency range of the audio data, the second frequency range different from the first frequency range, detect that a presentation rate of the monitored media is increased relative to a reference version of the media in response to the second peak being greater than the first peak, generate a signature corresponding to the monitored media, and transmit the signature to a media monitoring entity to credit the monitored media based on the presentation rate.