Binaural Sound Spatialization via Iterative Filter Optimization
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Solution Overview
Problem
Existing spatial sound reproduction techniques require extraction of interaural delays, which increases computational resources and doubles the number of filters needed for decoding, limiting the quality of sound rendering with a low number of channels.
Innovation Solution
A method for optimizing decoding filters and encoding gains by minimizing an error function through iterative optimization, allowing for good reconstruction of delays and amplitudes using a low number of channels, without the need for explicit delay extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If interaural delays are extracted from HRTF functions, then sound spatialization accuracy is improved, but computational resources increase and the number of decoding filters doubles
Solution Approach 1:
The patent combines the delay extraction and spatialization functions into a single optimized decoding filter. Instead of separating delay extraction as a distinct step that doubles the filter count, the invention integrates delay compensation directly into the decoding filter design, allowing both functions to be achieved with a reduced filter set.
Solution Approach 2:
The optimized decoding filters serve multiple functions simultaneously: they perform spatialization, delay compensation, and amplitude adjustment in a single operation. This multi-functionality eliminates the need for separate processing steps and reduces the overall computational complexity while maintaining spatialization accuracy.
2Manufacturing precision
If interaural delays are extracted and applied, then sound rendering quality is improved, but the number of channels and computational resources double
Solution Approach 1:
The invention applies delay compensation selectively through optimized filters rather than uniformly across all channels. By using partial action (applying delays only where necessary through the filter structure) rather than excessive action (applying to all channels separately), the patent achieves high sound rendering quality without doubling the computational load.
Solution Approach 2:
The patent optimizes filter parameters to simultaneously achieve delay compensation and spatialization. By changing the parameter optimization approach from separate delay extraction to joint filter optimization, the system achieves high rendering quality with reduced computational requirements.
3Productivity
If a low number of channels is used, then computational resources are reduced, but the quality of sound rendering deteriorates without explicit delay extraction
Solution Approach 1:
The invention changes the optimization parameters of the decoding filters to jointly optimize for both delay compensation and spatialization accuracy. This parameter optimization allows the system to achieve high sound rendering quality with a low number of channels, resolving the contradiction between computational efficiency and rendering quality.
Solution Approach 2:
The patent performs preliminary optimization of the decoding filter parameters to pre-compensate for delays and spatialization requirements. This preliminary action embedded in the filter design eliminates the need for separate delay extraction steps, maintaining high rendering quality with reduced channel count.
Data Source
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AI summary
The invention concerns sound spatialization with multichannel encoding for binaural reproduction on two loudspeakers, the spatial encoding being defined by encoding functions associated with multiple encoding channels and the decoding by applying filters for binaural reproduction. The invention provides for an optimization as follows: a) obtaining a original set of acoustic transfer functions particular to an individual's morphology (HRIR;HRTF), b) selecting spatial encoding functions ( g(?, ?,n) ) and/or decoding filters ( F(t,n) ), and c) through successive iterations, optimizing the filters associated with the selected encoding functions or the encoding functions associated with the selected filters, or jointly the selected filters and encoding functions, by minimizing an error (c(HRIR,HRIR*)) calculated based on a comparison between: the original set of transfer functions (HRIR), and a set of reconstructed transfer functions (HRIR*) from encoding functions and decoding filters, whether optimized and/or selected.