Automatic Audio Equalization Using Microphone Phase Differences
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Solution Overview
Problem
Manual audio equalization is cumbersome and requires significant user knowledge, making it difficult for average users to achieve high-quality audio output in various room environments without repeated setup and calibration.
Innovation Solution
An automated audio equalization system using microphones integrated into electronic devices, which measure phase differences and relative amplitudes to adjust frequency responses without user input, employing machine learning and acoustical models to learn and correct for room positions and reflections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual audio equalization is performed, then audio output quality can be improved, but user time and effort are significantly increased
Solution Approach 1:
The system uses the electronic device's own microphones to capture audio output and automatically perform equalization adjustments without requiring external measurement equipment or user intervention. The device self-calibrates by analyzing its own acoustic environment and applying corrections autonomously.
Solution Approach 2:
The patent replaces the manual mechanical process of equalization adjustment with an automated computational system. Machine learning models and acoustic transfer function calculations substitute for manual tuning, converting a labor-intensive process into an automatic computational task.
2Manufacturing precision
If manual audio equalization is performed, then audio output quality can be improved, but user knowledge requirements are significantly increased
Solution Approach 1:
The system performs equalization automatically using built-in microphones and processing algorithms, eliminating the need for users to understand acoustic theory, measurement techniques, or equalization concepts. The device handles the entire process independently.
Solution Approach 2:
The patent introduces machine learning models and acoustic transfer function calculations as intermediaries between the raw audio output and the final equalized signal. These computational layers translate complex acoustic measurements into automatic adjustments, shielding users from technical complexity.
3Manufacturing precision
If manual equalization is performed, then audio quality can be adjusted for specific room conditions, but the process must be repeated when room or placement changes
Solution Approach 1:
The system continuously monitors the acoustic environment using the electronic device's microphones and dynamically adjusts equalization parameters in real-time. This continuous adaptation ensures optimal audio quality regardless of changes in room conditions or device placement, eliminating the need for repeated manual calibration.
4Extent of automation
If automated audio equalization is implemented, then user interaction is eliminated, but system complexity is increased
Solution Approach 1:
The patent leverages the electronic device's existing microphones, which were originally designed for other purposes (such as voice recognition or environmental sound capture), and repurposes them for acoustic measurement and equalization. This multi-functional use of existing components automates equalization without adding dedicated hardware.
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
Enables high-quality audio output automatically, independent of user interaction, by continuously adapting to changes in room environments and device positions, improving listening experiences without the need for manual calibration.
Implementation Method 1
obtain a collection of audio content signals including receiving outputted audio content at each microphone of the plurality of microphones
Implementation Method 2
determine from the collection of audio content signals a plurality of phase differences between microphones of the plurality of microphones
Implementation Method 3
obtain a frequency correction from a correction database based on the determined acoustic transfer function and based on the obtained feature vector; applying the obtained frequency correction to the subsequent audio output
Data Source
AI summary
The various implementations described herein include methods, devices, and systems for automatic audio equalization. In one aspect, a method is performed at an electronic device that includes speakers, microphones, processors and memory. The electronic device outputs audio user content from the speakers and automatically equalizes subsequent audio output of the device without user input. The automatic equalization includes: (1) obtaining audio content signals, including receiving outputted audio content at each microphone; (2) determining from the audio content signals phase differences between microphones; (3) obtaining a feature vector based on the phase differences; (4) obtaining a frequency correction from a correction database based on the obtained feature vector; and (5) applying the obtained frequency correction to the subsequent audio output.