Adaptive Filter Encoding for Polyphonic Audio
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Solution Overview
Problem
Current multi-channel audio encoding techniques require high bit rates to maintain quality, especially at low frequencies, and often result in perceptual artifacts such as stereo image instability and spectral null-related issues, limiting their effectiveness in low bit rate applications like mobile communication systems.
Innovation Solution
The method involves combining channel signals into a main signal and applying adaptive filters with gain and shape constraints to reconstruct the channels, reducing perceptual artifacts and maintaining low bit rates by optimizing filter coefficients to preserve energy and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If adaptive filters are applied to reconstruct channel signals from a main signal, then audio quality is improved, but bit rate increases due to transmission of filter parameters
Solution Approach 1:
The patent applies parameter changes by optimizing filter coefficients under perceptual constraints and transmitting only essential filter parameters along with the main signal. The filter parameters are designed to be compact representations that enable high-quality reconstruction without requiring full transmission of channel signals, thus improving audio quality while controlling bit rate.
2Stability of the object's composition
If conventional multi-channel encoding is used, then stereo image stability is maintained, but bit rate requirements increase significantly
Solution Approach 1:
The patent merges multiple channel signals into a single main signal that contains the essential information for all channels. By combining the channels and using adaptive filters with perceptual constraints at the decoder, the system maintains stereo image stability while significantly reducing the bit rate requirement, as only one main signal and compact filter parameters need to be transmitted.
3Measurement precision
If filter coefficients are optimized without perceptual constraints, then reconstruction accuracy is improved, but perceptual artifacts increase
Solution Approach 1:
The patent changes the optimization criteria for filter coefficients by incorporating perceptual constraints into the optimization process. Instead of purely mathematical accuracy metrics, the filter coefficients are optimized to minimize perceptual artifacts while maintaining acceptable reconstruction accuracy. This results in filters that produce naturally sounding output without annoying artifacts.
Solution Approach 2:
The patent converts the potential harm of perceptual artifacts into a benefit by using perceptual constraints during filter optimization. The constraints are designed to prevent the generation of perceptually annoying artifacts while maintaining reconstruction quality, thus turning what could be a harmful effect into a controlled and beneficial optimization criterion.
Data Source
AI summary
Signals of different channels are combined into one mono signal. A set of adaptive filters, preferably one for each channel, is derived in a respective filter adaptation unit. When an adaptive filter is applied to the mono signal it reconstructs the signal of the respective channel under a perceptual constraint. The perceptual constraint is a gain and/or shape constraint. The gain constraint allows the preservation of the relative energy between the channels while the shape constraint allows more stability by avoiding unnecessary filtering of spectral nulls. The transmitted parameters are the mono signal, in encoded form, and the parameters of the adaptive filters, preferably also encoded. The receiver reconstructs the signal of the different channels by applying the adaptive filters and possibly some additional post-processing.