Subband Modal Processor for Low-Cost Resonant Reverb
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Solution Overview
Problem
The computational cost of implementing modal reverberators and processors is high due to the large number of modes in acoustic systems, requiring thousands of resonant filters, which is inefficient and costly in terms of computational resources.
Innovation Solution
The implementation of a parallel sum of resonant filters is optimized by processing input signals in frequency subbands with non-overlapping pass bands, using downsampling, heterodyning, and adjusting mode frequencies and gains to reduce computational requirements, and incorporating a wideband residual filter to account for energy outside assigned subbands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large number of resonant filters are used to accurately model acoustic spaces, then modeling precision is improved, but computational cost increases
Solution Approach 1:
The frequency spectrum is divided into multiple subbands, with each subband processed by a separate modal reverberator instance. This segmentation allows each subband to use fewer modes while collectively maintaining overall spectral accuracy, thereby reducing computational cost per subband while preserving total modeling precision.
Solution Approach 2:
The problem is transformed from the time domain to the frequency domain through FFT-based subband processing. By operating in the frequency domain and processing independent subbands, the system achieves computational efficiency while maintaining accurate acoustic modeling across the full spectrum.
2Productivity
If the sampling rate is reduced to lower computational cost, then processing speed is improved, but signal fidelity may deteriorate
Solution Approach 1:
The audio signal is segmented into frequency subbands before downsampling. Each subband is processed independently at its appropriate sampling rate, preserving signal fidelity within each band while enabling overall computational efficiency through parallel processing of multiple lower-rate subbands.
Solution Approach 2:
Different sampling rates are applied to different frequency subbands according to their specific requirements. Lower frequency subbands use lower sampling rates while higher frequency subbands maintain higher sampling rates, optimizing the balance between processing speed and signal fidelity for each local frequency region.
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
This approach significantly reduces the computational cost by processing mode filters at a lower sampling rate, achieving efficient and accurate audio processing with reduced MIPS requirements, while maintaining interactive control over acoustic features.
Implementation Method 1
The implementation of a parallel sum of resonant filters is optimized by processing input signals in frequency subbands with non-overlapping pass bands, using downsampling, heterodyning, and adjusting mode frequencies and gains to reduce computational requirements
Data Source
AI summary
The implementation of modal processors, which involve the parallel combination resonant filters, may be costly for applications such as artificial reverberation that can require thousands of modes. In one embodiment, the input signal is decomposed into a plurality of subbands, the outputs of which are downsampled. In each downsampled band, resonant filters are applied at the downsampled sampling rate, and their output is upsampled and filtered to form the band output. In these and other embodiments, a feature of responses of the mode filters have been optimized to minimize an aspect of a residual error after a point in time.