Audio Control System for Multi-Channel Spatial Emulation
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Solution Overview
Problem
Existing audio systems struggle to efficiently emulate the spatial characteristics of multi-channel audio sources on mono or stereo systems, requiring manual calibration and being time-consuming and inefficient.
Innovation Solution
An audio control system that uses a trained machine learning model to generate a frequency band energy representation and determine the strength of correlation between channels, allowing for automatic reformatting of multi-channel audio inputs into multi-dimensional signals that reflect the spatial characteristics of the original source, utilizing banks of auditory filters and correlator resources to adjust sound creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration is used to reformat multi-channel audio to mono/stereo, then the spatial characteristics can be preserved, but the process is time-consuming and inefficient
Solution Approach 1:
The system performs automatic reformatting without requiring manual calibration by a human operator. The audio signal is processed through the reformatting circuitry that automatically analyzes multi-channel audio and converts it to mono or stereo while preserving spatial characteristics, eliminating the need for manual intervention and significantly improving processing efficiency
Solution Approach 2:
The patent replaces manual calibration processes with an automated electronic system. The reformatting circuitry uses electronic signal processing to analyze correlation between channels and generate appropriate mixing signals, substituting the mechanical/manual calibration process with an automated electronic approach that maintains accuracy while improving speed
2Adaptability or versatility
If multi-channel audio is reformatted to mono or stereo, then compatibility with limited output systems is improved, but spatial characteristics are lost
Solution Approach 1:
The system applies different processing to different frequency bands and channels. The reformatting circuitry analyzes correlation characteristics of individual channels and applies appropriate mixing strategies to preserve spatial information locally in each frequency band, rather than applying a uniform transformation that would lose spatial characteristics
Solution Approach 2:
The patent transforms the audio signal from multi-channel spatial distribution into a mono or stereo format that encodes spatial characteristics through amplitude panning and correlation coding. The system uses the intensity and correlation of audio signals between channels to create a multi-dimensional representation that preserves spatial perception in a reduced channel format
3Productivity
If automatic reformatting is implemented, then processing efficiency is improved, but complexity of the audio control system increases
Solution Approach 1:
The reformatting circuitry is divided into distinct functional blocks: correlation analysis circuitry that determines channel relationships, mixing circuitry that combines channels based on correlation data, and output circuitry that generates the final mono or stereo signal. This segmentation allows each component to perform a specific function efficiently, managing overall system complexity through modular design
Data Source
AI summary
In some examples, an audio control system can include a first set of resources, a second set of resources and a controller. The first set of resources can generate a frequency energy band representation of a multi-channel source audio input. Additionally, the second set of resources can determine at least a value representing a strength of correlation between multiple channels of the multi-channel source audio input. Moreover, the audio output controller can determine a set of control parameters for tuning sound creation from an audio signal generator to reflect a set of spatial characteristics of the source audio input, based on the frequency energy band representation and the first value.