Networked Speaker Tuning Using Chirp Response Equalization
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Solution Overview
Problem
Large-scale networked audio systems in environments like conference rooms face challenges in tuning due to complexity, requiring expert teams for setup and configuration, and existing methods fail to accurately represent multiple speakers and detect feedback effectively.
Innovation Solution
A method that identifies multiple speakers and microphones on a network, provides sequential test signals to each amplifier channel, and automatically tunes speaker output parameters based on signal analysis, establishing background noise levels and noise spectra, using a processor to optimize settings for optimal audio performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multiple speakers are tested simultaneously with the same test signal, then the testing process is simplified, but the feedback from individual speakers cannot be accurately detected
Solution Approach 1:
The patent divides the testing process into two distinct phases: first, simultaneous testing with identical test signals to simplify the process; second, sequential testing with different test signals to accurately detect individual speaker feedback. This segmentation resolves the contradiction by applying different testing strategies for different measurement goals.
Solution Approach 2:
The patent changes the test signal parameters (frequency, type) when transitioning from simultaneous testing to sequential testing. By using different test signal characteristics in different phases, the system can both simplify the overall process and accurately measure individual speaker properties.
2Reliability
If expert teams manually setup and test audio equipment, then audio quality can be optimized, but the installation time and complexity increase significantly
Solution Approach 1:
The patent implements an automated tuning system where the audio equipment self-configures and self-optimizes by analyzing test signals and automatically adjusting parameters. This eliminates the need for expert teams while maintaining audio quality optimization, thereby resolving the contradiction between reliability and time loss.
Solution Approach 2:
The system uses feedback from microphone detections of test signals to automatically adjust speaker parameters. This closed-loop feedback mechanism enables automated optimization of audio quality without requiring manual expert intervention, reducing installation time while maintaining reliability.
3Device complexity
If a single test signal is used for all speakers, then the configuration process is simplified, but the unique characteristics of each speaker cannot be captured
Solution Approach 1:
The patent segments the configuration process into two parts: an initial simplified phase using a single test signal for all speakers, followed by a detailed phase using individualized test signals for each speaker. This segmentation allows the system to balance configuration simplicity with tuning accuracy.
Solution Approach 2:
The system performs preliminary configuration using a single test signal to establish basic settings for all speakers before conducting detailed individual tuning. This preliminary action reduces overall complexity while preserving the capability for precise individual parameter adjustment.
Data Source
AI summary
An example method of operation may include identifying speakers and microphones connected to a network controlled by a controller, assigning a preliminary output gain to the speakers used to apply test signals, measuring ambient noise detected from the microphones, recording chirp responses from all microphones simultaneously based on the test signals, deconvolving all chirp responses to determine a corresponding number of impulse responses, and measuring average sound pressure levels (SPLs) of each of the microphones to obtain a SPL level based on an average of the SPLs.