Audio Watermark Encoding in the Frequency Domain for Compression Robustness
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Solution Overview
Problem
In the field of audio, it is difficult to prove the ownership of a sound effect or audio piece, and existing watermarks are not robust enough to withstand audio compression and maintain inaudibility.
Innovation Solution
An encoding method converts a text watermark to an image watermark and then to an audio watermark, embedding it into the audio using discrete cosine transform and inverse discrete cosine transform, while a decoding method extracts and verifies the watermark using normalized cross correlation and singular value decomposition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a traditional audio watermark is embedded directly into the audio signal, then the watermark can be easily embedded, but the watermark lacks robustness against audio compression and processing
Solution Approach 1:
The patent transforms the watermark embedding process from the time domain to the frequency domain using Discrete Cosine Transform (DCT). By converting the audio signal and embedding the watermark in the frequency domain, the system achieves greater robustness against compression and processing while maintaining manageable encoding complexity through efficient DCT-based operations.
2Reliability
If the watermark is embedded with high strength to improve robustness, then the watermark becomes more resistant to compression, but the watermark becomes audible and degrades audio quality
Solution Approach 1:
The patent embeds the watermark selectively in specific frequency bands rather than uniformly across the entire audio spectrum. By analyzing the audio signal's frequency characteristics and embedding the watermark in regions with appropriate energy levels, the system achieves robust watermarking while maintaining high audio quality and avoiding audible artifacts.
Solution Approach 2:
The system dynamically adjusts the watermark embedding strength based on the local energy characteristics of different frequency bands. By changing the embedding parameter according to the audio signal's properties, the watermark achieves sufficient robustness without causing audible degradation, as the embedding strength is optimized for each frequency region.
3Object-affected harmful factors
If the watermark is embedded with low strength to maintain inaudibility, then the audio quality is preserved, but the watermark becomes vulnerable to removal during compression
Solution Approach 1:
By operating in the frequency domain through DCT transformation, the system achieves efficient watermark embedding at low strengths. The frequency-domain representation allows the watermark to be distributed across multiple coefficients, providing robustness against compression while maintaining inaudibility, as the transform enables precise control over where and how the watermark energy is distributed.
4Ease of manufacture
If a simple text watermark is used, then the implementation is straightforward, but the watermark lacks sufficient robustness and can be easily removed
Solution Approach 1:
The patent introduces an image watermark as an intermediary representation between the original text watermark and the final audio embedding. The text watermark is first converted to an image watermark, which is then transformed and embedded in the audio frequency domain. This intermediary step enhances robustness while maintaining implementation feasibility through standardized image processing techniques.
Solution Approach 2:
The system transforms the watermark through multiple representations (text to image to frequency-domain audio coefficients), changing its parameter form at each stage. This multi-stage transformation process significantly enhances the watermark's robustness against removal and compression, while each transformation step uses well-established algorithms that keep implementation complexity manageable.
Data Source
AI summary
An encoding method for embedding a watermark into an audio is provided. A text watermark and an original audio are obtained. The text watermark is converted to an image watermark. The original audio is converted from a time domain to a frequency domain to generate a pre-process audio. The image watermark is embedded into the pre-processed audio to generate an encoded audio. The encoded audio is converted from the frequency domain to the time domain to generate an watermarked audio.