Audio Fingerprint Temporal Alignment for Live Event Identification
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Solution Overview
Problem
Conventional audio identification schemes fail to accurately generate a reference audio fingerprint for continuous audio signals, particularly those from events like concerts or live performances, due to their inability to combine test audio fingerprints in real-time and dynamically update databases for efficient access.
Innovation Solution
A system that generates a complete reference fingerprint for an audio signal by temporally aligning and combining test audio fingerprints from multiple client devices, allowing for real-time identification and dynamic database updates, even with non-continuous samples due to copyright or technical limitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional audio identification schemes are used to generate reference fingerprints for live events, then the system can identify audio signals, but it cannot accurately represent the complete audio signal due to inability to combine test fingerprints from multiple sources
Solution Approach 1:
The system divides the audio signal representation into multiple test audio fingerprints captured by different client devices at different locations and times. Each test fingerprint represents a segment of the complete audio signal, and these segments are later combined to form the complete reference fingerprint for the live event.
Solution Approach 2:
The system merges multiple test audio fingerprints from different client devices by temporally aligning them and combining their data. This merging process creates a comprehensive reference fingerprint that accurately represents the complete audio signal from the live event, overcoming the limitations of individual test fingerprints.
2Adaptability or versatility
If the system captures audio fingerprints in real-time from live events, then it can identify audio signals from events, but it cannot obtain reference fingerprints in advance like pre-recorded content
Solution Approach 1:
The system performs preliminary actions by capturing and storing test audio fingerprints from multiple client devices during the live event. These test fingerprints are collected and temporarily stored, allowing the reference fingerprint to be generated immediately after the event without requiring advance preparation or post-event processing delays.
Solution Approach 2:
The system maintains continuous capture of audio fingerprints throughout the live event, ensuring that test fingerprints are continuously collected from multiple sources. This continuous action ensures complete coverage of the audio signal and enables immediate generation of the reference fingerprint once the event concludes.
3Reliability
If multiple test audio fingerprints are combined to create a reference fingerprint, then the identification accuracy improves, but the computational complexity and database update requirements increase
Solution Approach 1:
The system implements self-service by automatically temporally aligning and combining test audio fingerprints from multiple client devices without requiring manual intervention. The database is automatically updated with the generated reference fingerprint, and the system can independently identify audio signals by comparing new test fingerprints against the stored reference, reducing operational overhead.
Solution Approach 2:
The system uses feedback mechanisms where test audio fingerprints are continuously captured, compared against the reference fingerprint, and used to verify identification accuracy. This feedback loop ensures reliable identification while optimizing the database update process by only updating when necessary based on identification results.
Data Source
AI summary
An audio identification system generates a reference audio fingerprint associated with an event. The reference audio fingerprint is generated from samples of an audio signal associated with the event captured by multiple devices. To generate the reference audio fingerprint, fingerprints are generated from each sample, and the generated fingerprints are temporally aligned. Fingerprints associated a temporally overlapping portion of the audio signal are averaged, and the average value is associated with the temporally overlapping portion of the audio signal and included in the reference audio fingerprint. The reference audio fingerprint is stored along with identifying information, such as an event name, an event time, an event date, or other information describing the event associated with the audio signal from which the samples were captured.