Multi-Dimensional Microphone Motion Check for Audio Calibration
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Solution Overview
Problem
Existing media playback systems face challenges in calibrating playback devices to optimize sound quality in varying environments, as acoustics can significantly affect sound transmission, leading to frequency response issues that current calibration methods fail to adequately address.
Innovation Solution
A method involving a recording device that detects and analyzes sound waves emitted by playback devices, using motion data to determine sufficient translation across the listening environment, and applies a calibration profile to adjust the frequency response based on environmental acoustics, identifying and remedying error conditions such as insufficient motion or background noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current calibration methods are used, then calibration process is simple, but frequency response accuracy is insufficient due to inadequate addressing of environmental acoustics
Solution Approach 1:
The system performs preliminary actions by having the user move the recording device through the listening environment before calibration. This motion data is collected and analyzed in advance to validate that sufficient translation has occurred, ensuring the recording device has captured representative acoustic information from multiple positions. This preliminary validation step prevents inaccurate calibration while maintaining a user-friendly process.
Solution Approach 2:
The system implements feedback by monitoring motion data during calibration and comparing it against thresholds for sufficient translation. The system provides real-time feedback to the user about whether the recording device has moved enough, and can prompt the user to continue moving or retry the calibration. This feedback loop ensures frequency response accuracy without requiring complex manual adjustment procedures.
2Measurement precision
If motion validation is implemented during calibration, then calibration accuracy is improved, but calibration process time increases
Solution Approach 1:
The system applies preliminary anti-action by detecting and preventing calibration errors before they occur. Motion validation is performed continuously during the calibration process, and if insufficient motion is detected, the system prompts the user to move the recording device before proceeding. This prevents wasted calibration time and ensures accuracy without requiring multiple retry attempts.
Solution Approach 2:
The system uses partial action by implementing motion validation only for the specific translation movements required for accurate calibration, rather than requiring exhaustive exploration of the entire environment. The system determines sufficient translation based on predefined thresholds and proceeds with calibration once those thresholds are met, balancing accuracy with time efficiency.
3Reliability
If multi-dimensional motion check is performed, then calibration reliability is enhanced, but system complexity increases
Solution Approach 1:
The system applies universality by using a single recording device that performs multiple functions: capturing acoustic information, tracking motion through sensors, and providing user interface feedback. The motion validation system checks multiple dimensions (horizontal and vertical translation) using the same hardware components, eliminating the need for separate specialized devices and reducing overall system complexity while enhancing calibration reliability.
Solution Approach 2:
The system implements self-service by having the recording device automatically monitor its own motion and validate whether sufficient translation has occurred during calibration. The device uses its built-in motion sensors to track its position and compares this data against calibration requirements, eliminating the need for external monitoring equipment or complex manual tracking systems.
Data Source
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AI summary
Examples described herein involve validating motion of a microphone during calibration of a playback device. An example implementation involves receiving motion data indicating movement of a recording device while the recording device was recording a calibration sound emitted by one or more playback devices in a given environment during a calibration period. The example implementation also involves determining that sufficient vertical translation of the recording device occurred during the calibration period. The example implementation further involves determining that sufficient horizontal translation of the recording device occurred during the calibration period. The implementation involves sending, by the computing device to one or more playback devices, a message indicating that sufficient translation of the recording device occurred during the calibration period in vertical and horizontal directions.