Speech Audio Watermarking via Spectral Channel Masking
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Solution Overview
Problem
Existing audio watermarking systems poorly perform for speech and speech-like audio due to their unique temporal and spectral burstiness, leading to inaccurate listener ratings and potential career or program cancellations, as they fail to recognize the specific design requirements for these challenging types of audio.
Innovation Solution
A tailored watermarking architecture that optimizes symbol duration and spectral width to match the characteristics of speech, using multiple spectral channels with redundant encoding and error correction, ensuring symbols are minimally perceptible and robust against environmental noise, with symbols designed to be as benign as possible to avoid audibility issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a generic audio watermarking system is used, then it can handle general audio signals, but it performs poorly for speech and speech-like audio due to their unique temporal and spectral burstiness
Solution Approach 1:
The patent applies local quality by designing specific watermarking parameters (symbol duration, spectral width, energy distribution) tailored to speech-like audio characteristics. The system analyzes the temporal and spectral burstiness of speech and adjusts watermarking parameters locally to match these properties, rather than using a one-size-fits-all approach. This enables the watermarking system to achieve high reliability specifically for speech-like audio while maintaining adaptability across different audio types.
2Reliability
If watermark energy is increased to improve detection robustness, then decoding reliability improves, but the watermark becomes more perceptible to listeners
Solution Approach 1:
The patent applies dynamics by making the watermark energy adaptive rather than static. The system dynamically adjusts watermark energy based on the local masking properties of the speech signal. In regions where speech energy is high and masking is strong, the watermark energy can be increased without becoming perceptible. In regions with low speech energy or weak masking, the watermark energy is reduced to maintain imperceptibility. This dynamic adaptation allows the system to achieve high decoding reliability while maintaining low audibility.
Solution Approach 2:
The patent applies parameter changes by optimizing multiple watermarking parameters simultaneously - symbol duration, spectral width, energy distribution, and insertion timing. Rather than simply increasing overall watermark energy, the system changes these parameters to exploit the temporal and spectral structure of speech. By aligning symbol duration with speech phoneme boundaries and concentrating energy in spectrally quiet regions, the system achieves robust decoding without increasing perceptibility.
3Measurement precision
If symbol duration is extended to improve decoding accuracy, then watermark detection improves, but the watermark becomes more audible and less suitable for speech-like audio
Solution Approach 1:
The patent applies segmentation by dividing the watermark message into multiple short symbols that are inserted at different time locations within the speech signal. Rather than using a single long symbol, the system segments the watermark data and distributes it across multiple shorter symbols. This segmentation allows each symbol to be brief enough to remain imperceptible in speech, while the collective set of symbols provides sufficient information for accurate decoding through redundancy and error correction codes.
Solution Approach 2:
The patent applies another dimension by transitioning from time-domain symbol duration to a combined time-frequency domain approach. Instead of extending symbol duration in time, the system uses multiple short symbols distributed across different time and frequency locations. By exploiting the frequency dimension (spectral width) and the temporal distribution of multiple symbols, the system achieves the same decoding accuracy that would require a single long symbol, while maintaining imperceptibility through short duration.
4Reliability
If multiple spectral channels with redundant encoding are used, then robustness against noise and errors improves, but device complexity increases
Solution Approach 1:
The patent applies universality by designing a multi-channel watermarking system where the same watermarking algorithm and symbol structure are used across multiple spectral channels. Rather than implementing different complex algorithms for each channel, the system uses a universal framework that distributes watermark symbols across multiple frequency bands. This multi-functional approach provides robustness against noise and errors (since watermarks can be recovered from any single channel) while keeping the overall system complexity manageable through algorithmic uniformity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution significantly improves the accuracy of watermarking for speech and speech-like audio, ensuring reliable decoding even in adverse conditions, thereby preventing misattributions of listener ratings and program cancellations.
Implementation Method 1
The watermark encoding method may take advantage of perceptual masking of the host audio signal to hide the watermark. Perceptual masking refers to a process where one sound is rendered inaudible in the presence of another sound.
Data Source
AI summary
A method to watermark an audio signal may include receiving watermark data payload information, converting the watermark data payload information into a watermark audio signal including one or more watermark messages corresponding to the watermark data payload information, and inserting the one or more watermark messages into multiple spectral channels of the audio signal, wherein each of the multiple spectral channels occupies a different frequency range, wherein, once an audio segment has been inserted into a spectral channel of the audio signal, amplitude of the audio segment is held constant for the time duration of the audio segment such that a first portion of the audio segment is masked by the audio signal and a second portion of the audio segment is not masked by the audio signal.