Calibration Error Detection in Playback Devices
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Solution Overview
Problem
Existing media playback systems face challenges in accurately calibrating playback devices in diverse environments due to interference from error conditions such as background noise, improper microphone orientation, and inadequate movement during calibration, which can affect the quality of audio experience.
Innovation Solution
A network device with a microphone and processor identifies error conditions by analyzing audio and motion data during calibration, suspending the process and providing feedback to users on necessary corrections, ensuring optimal calibration and audio quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If calibration is performed in diverse environments, then the system can adapt to different playback settings, but error conditions such as background noise, improper microphone orientation, and inadequate movement can interfere with calibration accuracy
Solution Approach 1:
The system performs preliminary detection of error conditions (background noise, microphone orientation, movement adequacy) before completing the calibration process. By identifying these potential interference factors in advance, the system can prevent calibration errors and ensure accurate measurements across diverse environments.
Solution Approach 2:
The system provides feedback to users about detected error conditions during calibration, such as notifying them of background noise interference, improper microphone orientation, or insufficient movement. This feedback mechanism allows users to correct the identified issues and retry calibration, thereby maintaining both adaptability to diverse environments and calibration accuracy.
2Measurement precision
If the calibration process is suspended upon detecting error conditions, then calibration accuracy is maintained, but the calibration time increases due to potential retries
Solution Approach 1:
The system provides immediate feedback to users when error conditions are detected during calibration, informing them of the specific issue (e.g., background noise, improper orientation). This enables users to quickly understand and correct the problem, reducing the time lost compared to undetected calibration failures that would require complete retries.
Solution Approach 2:
The system empowers users to self-correct calibration errors by providing clear guidance about the detected issues. Users can independently adjust microphone orientation, reduce background noise, or increase movement as directed by the system feedback, eliminating the need for technical support intervention and minimizing overall calibration time.
3Ease of operation
If the system provides detailed feedback about error conditions to users, then users can make informed corrections, but the system complexity increases
Solution Approach 1:
The error detection and feedback system is segmented into distinct functional modules: background noise detection, microphone orientation detection, movement adequacy detection, and feedback generation. Each module independently handles a specific aspect of error detection, making the overall system easier to implement, maintain, and debug despite the comprehensive functionality provided.
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
The solution effectively identifies and addresses error conditions, ensuring accurate calibration of playback devices and enhancing the audio experience by providing users with actionable feedback to remedy identified issues.
Implementation Method 1
a microphone of a network device being used for the calibration detects an audio signal
Data Source
AI summary
Examples described herein involve identifying one or more error conditions during calibration of one or more playback devices in a playback environment. A microphone of a network device may detect and sample an audio signal while the one or more playback devices in the playback environment plays a calibration tone. A processor of the network device may then receive, from the microphone, a stream of audio data. The audio data may include an audio signal component and a background noise component. As a subset of the audio data is received, the processor may identify based on the audio data, the one or more error conditions. The processor may then cause a graphical display to display a graphical representation associated with the identified error condition.