Microphone Array Azimuth Detection for Stable Conference Audio
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Solution Overview
Problem
Existing azimuth estimation methods in video conferencing systems are not fast and stable, failing to provide accurate azimuth degree determination.
Innovation Solution
An audio processing method involving a microphone array and processor to compute frequency array data, determine power sequences, and calculate the difference between maximum and minimum power values to identify the source degree relative to the microphone array.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing azimuth estimation methods are used, then the system can provide basic audio processing, but the azimuth degree determination is not fast and stable
Solution Approach 1:
The audio processing is segmented into distinct stages: capturing audio data through multiple microphones, converting to frequency domain data via FFT, calculating power spectrum, determining azimuth degrees by comparing phase differences, and computing power sequences. This segmentation allows each stage to be optimized independently, improving both accuracy and stability of azimuth estimation.
Solution Approach 2:
The system performs preliminary actions by pre-calculating frequency array data from audio data, and pre-determining the relationship between phase differences and azimuth degrees before actual measurement. This preliminary processing establishes a foundation that enables faster and more stable real-time azimuth estimation without compromising accuracy.
2Measurement precision
If complex audio processing computations are performed to improve accuracy, then measurement precision improves, but computation time increases
Solution Approach 1:
The invention extracts only the essential computational elements needed for azimuth estimation: capturing audio data, performing FFT to obtain frequency data, calculating power spectrum, and determining azimuth from phase differences. By extracting and focusing on these critical computations while eliminating unnecessary processing steps, the system achieves high accuracy with reduced computation time.
Solution Approach 2:
The system changes parameters by working in the frequency domain instead of time domain for azimuth calculation. By transforming audio data to frequency array data and computing power sequences, the method enables more efficient computation of azimuth degrees through phase difference analysis, reducing computational complexity while maintaining precision.
3Measurement precision
If noise interference is present in the audio environment, then measurement accuracy deteriorates, but the system must continue to operate
Solution Approach 1:
The invention converts the harmful effect of noise by using power sequence computation. By calculating the power spectrum and identifying the maximum power value, the system effectively filters out noise components and isolates the dominant sound source. This approach transforms noise interference into a benefit by using power comparison to automatically distinguish signal from noise, improving sound source identification accuracy in noisy environments.
Data Source
AI summary
An audio processing method includes the following steps of capturing audio data by a microphone array to compute frequency array data of the audio data; computing a power sequence of degrees by using the frequency array data; and computing a difference value between a maximum value of the power sequence of degrees and a minimum value of the power sequence of degrees to determine whether the degree corresponding to the maximum value is a source degree relative to the microphone array.