Audio Fingerprinting Using Stable Frequency Families
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Solution Overview
Problem
Existing fingerprinting technologies require larger storage space, processing power, and time to generate and analyze fingerprints, making them inefficient for managing vast libraries of audio files on consumer electronics devices.
Innovation Solution
The development of an audio fingerprinting technology that uses stable frequency families to create smaller fingerprints, reducing storage and processing requirements, and employs curve fitting and variation extraction to generate fingerprints efficiently, allowing for the management of hundreds or thousands of audio files on devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional fingerprinting technologies are used, then audio recording identification can be achieved, but storage space requirements increase and processing power consumption increases
Solution Approach 1:
The patent extracts only the essential frequency information from audio recordings to create fingerprints. By focusing on stable frequency families and their variations rather than analyzing the entire audio spectrum, the system generates compact fingerprints that require minimal storage space while maintaining identification accuracy.
Solution Approach 2:
The patent transforms audio recordings into a different parameter space by converting time-domain audio data into frequency-domain representations. By representing audio content through stable frequency families and their variations rather than raw audio samples, the system achieves efficient compression of fingerprint data.
2Measurement precision
If conventional fingerprinting technologies are used, then audio recording identification can be achieved, but processing power requirements increase
Solution Approach 1:
The patent extracts only the essential frequency information from audio recordings to create fingerprints. By focusing on stable frequency families and their variations rather than analyzing the entire audio spectrum, the system generates compact fingerprints that require minimal storage space while maintaining identification accuracy.
Solution Approach 2:
The patent transforms audio recordings into a different parameter space by converting time-domain audio data into frequency-domain representations. By representing audio content through stable frequency families and their variations rather than raw audio samples, the system achieves efficient compression of fingerprint data.
3Measurement precision
If conventional fingerprinting technologies are used, then audio recording identification can be achieved, but time to generate and analyze fingerprints increases
Solution Approach 1:
The patent extracts only the essential frequency information from audio recordings to create fingerprints. By focusing on stable frequency families and their variations rather than analyzing the entire audio spectrum, the system generates compact fingerprints that require minimal storage space while maintaining identification accuracy.
Solution Approach 2:
The patent transforms audio recordings into a different parameter space by converting time-domain audio data into frequency-domain representations. By representing audio content through stable frequency families and their variations rather than raw audio samples, the system achieves efficient compression of fingerprint data.
Data Source
AI summary
A method, apparatus and computer memory are provided for generating an audio fingerprint of an audio recording. A memory stores stable frequency family data corresponding to a plurality of stable frequency families. A processor curve fits audio recording data to at least one of the stable frequency families, extracts at least one variation from the curve fitted audio recording data, and creates the audio fingerprint of the audio recording from the at least one variation.