Audio Identification via Frequency-Domain Scale Normalization
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Solution Overview
Problem
Existing audio identification processes fail due to skewed speed and frequency-domain representations of audio signals, often caused by intentional alterations, processing errors, or Doppler shifts, leading to mismatched frequency-domain representations and impaired identification.
Innovation Solution
A method to normalize the query frequency-domain representation by determining a frequency peak within a predefined bin and transforming it to a predefined position, aligning it with reference frequency-domain representations, thereby facilitating accurate audio identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the audio signal is processed using conventional frequency-domain representation, then the identification process is simple, but the identification accuracy deteriorates due to skewed frequency representations caused by speed alterations or Doppler shifts
Solution Approach 1:
The patent applies preliminary normalization to the query frequency-domain representation before matching. By pre-adjusting the frequency peak positions to a standard reference scale, the system prepares the data in advance to compensate for speed alterations or Doppler shifts, thereby improving identification accuracy without adding complexity during the matching phase
Solution Approach 2:
The patent transforms the frequency-domain representation by changing the frequency scale parameter. Specifically, it identifies the frequency peak and rescales the entire frequency representation so that the peak aligns with a reference frequency position, effectively normalizing the skewed frequency data to match reference audio signatures
2Measurement precision
If the frequency-domain representation is normalized by transforming frequency peaks, then the matching accuracy improves, but the processing time increases
Solution Approach 1:
The patent extracts only the critical frequency peak information from the complete frequency-domain representation for normalization purposes. By focusing on identifying and transforming just the peak positions rather than processing the entire frequency spectrum, the system achieves accurate normalization with reduced computational overhead and faster processing time
Data Source
AI summary
A method includes receiving, by a computing system, an audio signal, where the audio signal defines a segment of media content over time. The method also includes establishing by the computing system, based on the received audio signal, a normalized query frequency-domain representation of the received audio signal. The method further includes matching, by the computing system, the normalized query frequency-domain representation of the received audio signal with a correspondingly normalized reference frequency-domain representation of a reference audio signal having an associated identity. The method additionally includes based on the matching, determining by the computing system that an identity of the received audio signal is the associated identity of the reference audio signal.