Microphone Calibration via Sound Source Direction Detection
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Solution Overview
Problem
Mobile devices with multiple microphones face calibration challenges due to shadowing effects and potential impairments, such as dust or user interference, which affect audio quality and require frequent recalibration to maintain signal balance across microphones.
Innovation Solution
A method and apparatus that determine the direction of sound sources using correlation time differences between microphone signals, calibrate signals based on expected signal relationships, and update calibration values over time to maintain optimal microphone performance without user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual calibration methods are used, then initial microphone calibration can be achieved, but frequent recalibration is required due to shadowing effects and impairments from dust or user interference
Solution Approach 1:
The system performs automatic self-calibration by analyzing audio signals captured from multiple microphones and directions, determining calibration values without user intervention. The processor continuously monitors microphone performance and adjusts calibration parameters automatically, eliminating the need for manual recalibration operations while maintaining stable audio quality.
Solution Approach 2:
The system implements feedback mechanisms where the processor analyzes the audio signals from multiple microphones, compares them against expected relationships, and automatically adjusts calibration values. This closed-loop feedback system continuously monitors and corrects for changes in microphone performance due to dust, wear, or positioning variations.
2Adaptability or versatility
If multiple microphones are used to improve audio quality, then audio recording capability is enhanced, but device complexity increases due to additional calibration requirements
Solution Approach 1:
The calibration system serves multiple functions: it calibrates microphone signal levels, compensates for shadowing effects, adjusts for directional variations, and adapts to changes over time. A single integrated calibration mechanism handles all these requirements, reducing overall system complexity despite having multiple microphones.
Solution Approach 2:
The system dynamically adjusts calibration parameters based on the direction and characteristics of audio signals. By changing calibration values in response to detected audio properties and microphone performance variations, the system maintains optimal audio quality without requiring complex hardware modifications.
3Measurement precision
If calibration values are updated frequently to maintain optimal performance, then audio quality consistency is improved, but processing time and computational load increase
Solution Approach 1:
The system performs calibration updates periodically based on detected changes in microphone performance or audio signal characteristics, rather than continuously. This periodic approach maintains audio quality consistency while reducing unnecessary processing during stable conditions, balancing precision with computational efficiency.
Solution Approach 2:
The processor uses feedback from audio signal analysis to determine when calibration updates are necessary. By monitoring changes in signal relationships and microphone performance, the system applies calibration corrections only when needed, minimizing processing time while maintaining consistent audio quality.
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
Improves microphone calibration accuracy and adaptability, ensuring consistent audio quality by automatically adjusting for changes caused by dust, wear, or user handling, and effectively compensates for impairments like blockages or distortions.
Implementation Method 1
determining at least one direction associated with the determined at least one audio source... determining a maximum correlation time difference between a pair of the at least part of the two microphone signals; determining a direction based on the maximum correlation time difference
Data Source
AI summary
An apparatus comprising: an input configured to receive at least two microphone signals associated with at least one acoustic source; an audio source determiner configured to determine from at least part of the at least two microphone signals at least one audio source based on the at least one acoustic source; an audio source direction determiner configured to determine at least one direction associated with the determined at least one audio source; a calibrator configured to calibrate at least one of the at least two microphone signals based on the at least one direction.