Audio Event Triggering via Spectral Peak Fingerprinting
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Solution Overview
Problem
Existing systems for processing streaming signals, such as audio signals, require costly hardware to analyze and trigger events effectively, limiting their deployment on lower-cost devices.
Innovation Solution
A method and system that utilize fingerprints associated with trigger points within a signal stream to detect and trigger events, reducing computational requirements by comparing predefined fingerprints with the signal stream, enabling event triggering on lower-cost hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Shazam technology is used to analyze streaming audio signals and calculate fingerprints, then accurate music track identification can be achieved, but high computational cost and expensive hardware are required
Solution Approach 1:
The patent extracts only the essential spectral peak information from the audio signal to create simplified fingerprints, rather than processing the entire audio spectrum. This extraction approach maintains identification accuracy while dramatically reducing computational requirements, enabling deployment on lower-cost hardware.
Solution Approach 2:
The audio signal is segmented into short time frames, and only specific spectral peaks within each frame are extracted and stored as fingerprint points. This segmentation strategy breaks down the complex task of full-signal analysis into manageable segments, reducing overall computational load while preserving key identification features.
2Reliability
If full audio signal processing is performed to ensure reliable event triggering, then high accuracy can be achieved, but processing time and computational resources increase
Solution Approach 1:
Fingerprints are pre-calculated and stored at specific time locations in the audio signal before real-time processing. During playback, the system only needs to compare incoming signal frames against these pre-computed fingerprints, significantly reducing real-time processing time while maintaining reliable event triggering accuracy.
Solution Approach 2:
The system processes only a subset of spectral information (specific spectral peaks) rather than the complete audio signal. This partial processing approach provides sufficient information for reliable event detection without the computational overhead of analyzing every aspect of the audio signal, thus reducing processing time while maintaining accuracy.
Data Source
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AI summary
The present invention relates to a method of triggering an event. The method includes receiving a signal stream, detecting a trigger point within the signal stream using a fingerprint associated with the trigger point and triggering an event associated with the detected trigger point.