Multi-Dimensional Microphone Motion Checks in Audio Calibration
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Solution Overview
Problem
Existing media playback systems face challenges in accurately calibrating audio devices in diverse environments due to variations in acoustics, leading to suboptimal sound transmission and quality.
Innovation Solution
A method involving a recording device that detects and analyzes sound waves emitted by playback devices during calibration, using motion data to determine sufficient translation in multiple dimensions, thereby adjusting the frequency response to compensate for environmental acoustics and ensuring effective calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If audio calibration is performed in diverse environments, then adaptability of the system is improved, but measurement precision deteriorates due to acoustic variations
Solution Approach 1:
The patent introduces motion validation in multiple dimensions (horizontal, vertical, rotational) to verify proper microphone movement during calibration. This multi-dimensional approach ensures that the calibration process captures acoustic variations across different spatial orientations, thereby maintaining measurement precision while adapting to diverse environmental acoustics.
Solution Approach 2:
The system implements feedback mechanisms by validating motion data against expected calibration patterns. The playback device receives motion information from the recording device and determines whether the motion falls within valid ranges, providing feedback to ensure calibration accuracy is maintained across different environments.
2Measurement precision
If motion validation is performed in multiple dimensions, then calibration accuracy is improved, but device complexity increases
Solution Approach 1:
The recording device and playback device are designed with multi-functional capabilities. The recording device not only captures audio but also tracks motion data across multiple dimensions. The playback device both plays calibration tones and validates the received motion information. This multi-functionality reduces the need for separate dedicated components, thereby managing complexity while enabling multi-dimensional validation.
Solution Approach 2:
Motion data serves as an intermediary between the physical movement of the recording device and the calibration accuracy determination. By validating this intermediate motion information against expected patterns, the system can assess calibration quality without requiring direct complex measurements of acoustic field variations in all dimensions.
3Reliability
If environmental acoustic factors are accounted for, then sound quality is improved, but calibration process time increases
Solution Approach 1:
The system performs preliminary motion validation during the calibration process by continuously monitoring motion data as the recording device moves through the environment. Rather than requiring separate post-calibration validation steps, the motion checks are integrated into the calibration workflow, allowing environmental acoustic factors to be accounted for while minimizing additional time expenditure.
Solution Approach 2:
The patent validates motion within defined valid ranges rather than requiring perfect or excessive precision in motion measurement. By accepting motion data that falls within acceptable thresholds rather than demanding exact positional accuracy, the system efficiently captures sufficient environmental acoustic information to improve sound quality without unnecessarily extending calibration time.
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
This approach enhances audio device calibration by accurately accounting for environmental factors, improving sound transmission and quality across different settings.
Implementation Method 1
a recording device that detects and analyzes sound waves emitted by playback devices during calibration
Data Source
AI summary
Examples described herein involve validating motion of a microphone during calibration of a playback device. An example implementation involves a control device receiving an indication that the control device will begin detecting audio signals emitted from playback devices as part of a calibration process. While the control device is detecting audio signals emitted from the playback devices, the control device receives a stream of motion data indicating movement of the control device. The control device processes a first subset of the stream of motion data to determine that the first subset of the stream of motion data indicates sufficient horizontal translation of the control device occurred. Based on determining that the first subset of the stream of motion data indicates sufficient horizontal translation of the control device, the control device processes a second subset of the stream of motion data.