Neural Network Audio Directionality Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies face challenges in providing a realistic and efficient perception of sound directionality, particularly in real-time scenarios like virtual and augmented reality, due to delays associated with processing audio signals for accurate localization.
Innovation Solution
A system utilizing a processor with associated memory to identify audio signals, calculate intermediate values, and feed them into a neural network to produce orienting audio outputs for each ear, which are then delayed accordingly to simulate the perception of directionality without the need for lookup tables, using techniques such as principal component analysis and stacked sparse autoencoders to reduce dimensionality and enhance processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional audio processing methods with lookup tables are used to achieve accurate sound directionality, then measurement precision is improved, but loss of time increases due to processing delays
Solution Approach 1:
The patent pre-calculates and stores HRTF data in a lookup table during system initialization or offline processing. This preliminary action allows the runtime audio processing to simply retrieve pre-computed directional filtering data without performing complex calculations in real-time, thus maintaining high directionality accuracy while minimizing processing delay.
Solution Approach 2:
The system performs dimensionality reduction on HRTF data in advance using principal component analysis (PCA) to identify the most significant components that capture the essential directional information. By pre-processing the HRTF data to extract key features, the system reduces the computational burden during real-time audio rendering while preserving accurate sound localization.
2Measurement precision
If complex HRTF processing is performed in real-time to achieve accurate sound localization, then measurement precision is improved, but productivity decreases due to computational complexity
Solution Approach 1:
The patent extracts and separates the complex HRTF processing into distinct components: the directional filtering characteristics are extracted from the full HRTF data and stored in a lookup table, while the actual audio rendering process only needs to apply these extracted filters. This extraction allows the system to maintain high localization accuracy while significantly improving processing speed by avoiding redundant computations.
Solution Approach 2:
The system transforms the full-resolution HRTF data into a reduced-parameter representation using principal component analysis, keeping only the most significant components that capture the essential directional information. This parameter reduction maintains accurate sound localization while dramatically reducing the computational complexity and processing time required for real-time audio rendering.
Data Source
AI summary
A system for creating a perception of directionality to an audio signal, the system including: a processor with an associated memory, the associated memory containing instructions, which when executed cause the processor to: identify an audio signal and an orientation to be applied to the audio signal; calculate intermediate values to reduce the dimensions of the audio signal and orientation; provide the intermediate values into a neural network, to produce a first and second orienting audio outputs; and provide the first orienting audio output to a first speaker and the second orienting audio output to a second speaker.