Telepresence Microphone Array Calibration Using Reverberant PSDs
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Solution Overview
Problem
Conventional methods for calibrating microphones and loudspeakers in telepresence conferencing systems are cumbersome, require human intervention, and are prone to errors due to inaccurate positioning and configuration.
Innovation Solution
Generate calibration filters for microphones and loudspeakers by deriving power spectral densities from reverberant sound fields, using existing system hardware to automatically calibrate without human involvement, insensitive to room configuration and hardware positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional calibration methods are used, then calibration can be performed, but the process is cumbersome and requires human intervention
Solution Approach 1:
The calibration system performs self-calibration automatically without requiring human intervention. The microphones and loudspeakers themselves generate and process calibration signals to derive calibration filters, eliminating the need for external calibration equipment or manual configuration by operators.
Solution Approach 2:
The patent replaces manual mechanical calibration processes with automated signal processing. Instead of physical adjustment of microphone positions or gain settings, the system uses computational algorithms to process audio signals and automatically adjust calibration parameters through digital signal processing.
2Measurement precision
If conventional calibration methods are used, then calibration can be performed, but positioning and configuration errors occur
Solution Approach 1:
The calibration system uses feedback mechanisms where microphones receive calibration signals from loudspeakers, and the system processes the returned audio signals to compute calibration filters. This closed-loop feedback allows the system to automatically compensate for positioning errors and configuration variations, improving both accuracy and reliability.
Solution Approach 2:
The system dynamically adjusts calibration parameters based on measured audio characteristics. By computing power spectral densities and deriving calibration filters from actual acoustic measurements, the system adapts to different room configurations and positioning scenarios, maintaining high measurement precision and reliability across varying conditions.
3Device complexity
If existing hardware is used for calibration, then device complexity is reduced, but calibration quality may be compromised
Solution Approach 1:
The existing microphones and loudspeakers in the telepresence system are made multi-functional by using them both for normal audio operations and for calibration purposes. The same hardware components that capture and reproduce audio also serve as the calibration measurement system, eliminating the need for separate calibration equipment while maintaining calibration quality.
Solution Approach 2:
The system creates virtual copies of acoustic measurements through signal processing. By recording calibration signals and computing power spectral densities from the audio signals, the system generates digital representations of acoustic characteristics that can be used for calibration without requiring physical measurement equipment or additional 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
Achieves accurate and automatic calibration of microphones and loudspeakers, ensuring high-quality directionally-sensitive audio signals and realistic spatialized output in telepresence systems.
Implementation Method 1
an audio signal generated by each loudspeaker of an array of loudspeakers
Implementation Method 2
a reverberant sound field based on an audio signal generated by each loudspeaker
Data Source
AI summary
Techniques of calibrating microphones and loudspeakers in a telepresence system includes generating calibration filters for microphones and/or speakers by deriving power spectral densities at each microphone from each loudspeaker. For example, a computer within an improved telepresence system can measure a raw impulse response function corresponding to each channel, i.e., each loudspeaker/microphone pair. The computer then extracts a sub-segment of each impulse response function between a start and finish time. The computer then generates a white-noise power spectral density for each channel based on the sub-segments. The calibration function for a microphone is then based on a reciprocal of the power spectral density averaged over the loudspeakers. The calibration function for a loudspeaker is then based on a reciprocal of the power spectral density averaged over the microphones.