Frequency-Domain Binaural Rendering With Variable-Order Subband Filtering
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Solution Overview
Problem
Binaural rendering for multi-channel audio signals requires high computational complexity, especially with long binaural room impulse response filters, leading to inefficiencies and increased computational demands, particularly in real-time processing environments.
Innovation Solution
The method involves processing audio signals using truncated subband filter coefficients derived from binaural room impulse response filters, performing fast Fourier transforms, and generating filtered subframes through multiplication and inverse fast Fourier transformations, while optimizing filter lengths based on characteristic information to reduce computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If long BRIR filters are used for binaural rendering, then sound quality is improved, but computational complexity increases
Solution Approach 1:
The patent divides the long BRIR filter into multiple subband filters operating in parallel across different frequency bands. Each subband filter processes a specific frequency range, allowing the overall filtering operation to be distributed and computed more efficiently than a single long-time-domain filter, thus reducing computational complexity while preserving sound quality.
Solution Approach 2:
The patent transforms the filtering operation from the time domain to the frequency domain using FFT. By converting the long BRIR filter and input signal into frequency domain representations, the convolution operation becomes element-wise multiplication, dramatically reducing computational complexity from O(N*M) to O(N log N + M log M) while maintaining the ability to reproduce long impulse response characteristics.
2Adaptability or versatility
If the number of input channels increases, then audio format capability is improved, but computational complexity increases enormously
Solution Approach 1:
The patent applies subband decomposition to multi-channel audio processing, where each channel is processed through parallel subband filters. This segmentation allows the system to handle multiple channels simultaneously with reduced per-channel computational load, as each subband operates independently and can be processed in parallel.
Solution Approach 2:
The patent creates a universal processing framework that handles both stereo and multi-channel formats through the same subband FFT-based filtering architecture. The system can adapt to different channel configurations (2.0, 5.1, 7.1, 22.2, etc.) without requiring separate processing paths, achieving format versatility while maintaining computational efficiency through the standardized frequency-domain approach.
3Manufacturing precision
If time-domain convolution is used for binaural filtering, then filtering accuracy is maintained, but computational complexity increases
Solution Approach 1:
The patent performs the convolution operation in the frequency domain instead of the time domain. By applying FFT to both the BRIR filter and input signal, the computationally intensive time-domain convolution is transformed into efficient element-wise complex multiplication in the frequency domain, reducing complexity while preserving filtering accuracy through the mathematical equivalence of convolution in time domain and multiplication in frequency domain.
Solution Approach 2:
The patent changes the representation parameters of the signals from time-domain samples to frequency-domain coefficients. This parameter transformation allows the same filtering operation to be performed with different computational characteristics, where the frequency-domain parameters enable faster processing through FFT-based algorithms while maintaining the physical accuracy of the binaural filtering effect.
Data Source
AI summary
The present invention relates to a method and an apparatus for binaural rendering an audio signal using variable order filtering in frequency domain. To this end, provided are a method for processing an audio signal including: receiving an input audio signal; receiving a set of truncated subband filter coefficients for filtering each subband signal of the input audio signal, the set of truncated subband filter coefficients being constituted by one or more FFT filter coefficients generated by performing FFT by a predetermined block size; generating at least one subframe for each subband; generating at least one filtered subframe for each subband; performing inverse FFT on the filtered subframe for each subband; and generating a filtered subband signal by overlap-adding the transformed subframe for each subband and an apparatus for processing an audio signal using the same.