Earphone Wind Noise Recognition Using Coherence Analysis
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Solution Overview
Problem
Existing wind noise recognition methods for earphones suffer from poor recognition accuracy and high recognition costs, particularly when using dual microphones, and fail to effectively identify wind noise during active noise cancellation modes.
Innovation Solution
The method employs the existing first microphone outside the ear and second microphone inside the ear to acquire signals, which are then frequency domain filtered and analyzed for coherence to determine the presence of wind noise, reducing hardware costs and improving recognition accuracy without the need for additional microphones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If wind noise recognition is performed using existing dual microphones (first microphone outside ear and second microphone inside ear), then hardware cost is reduced, but recognition accuracy is poor
Solution Approach 1:
The patent segments the wind noise recognition process into multiple independent steps: acquiring first microphone signal from external microphone, acquiring second microphone signal from internal microphone, performing frequency domain filtering on both signals, and calculating coherence between the filtered signals. This segmentation allows each step to be optimized independently, improving overall recognition accuracy while using existing dual microphones without adding hardware cost.
Solution Approach 2:
The patent introduces frequency domain filtering as an intermediary processing step between signal acquisition and coherence calculation. By filtering both the first microphone signal and second microphone signal in the frequency domain before coherence calculation, the method enhances the separation of wind noise characteristics from other sounds, thereby improving recognition accuracy without requiring additional microphones.
2Measurement precision
If frequency domain filtering is applied to both first microphone signal and second microphone signal before coherence calculation, then wind noise recognition accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent replaces time-domain signal processing with frequency-domain filtering using Fast Fourier Transform (FFT). This substitution allows for more efficient filtering operations and coherence calculation, as frequency-domain processing can leverage optimized mathematical algorithms that reduce computational complexity compared to traditional time-domain methods, thereby improving accuracy without proportionally increasing processing burden.
3Reliability
If coherence calculation is performed between first microphone signal and second microphone signal to identify wind noise, then wind noise can be detected, but false identification of other sounds as wind noise may occur
Solution Approach 1:
The patent performs preliminary frequency domain filtering on both the first microphone signal and second microphone signal before conducting coherence calculation. This preliminary action prepares the signals by enhancing wind noise characteristics and suppressing other sound components, ensuring that the subsequent coherence calculation more accurately reflects true wind noise presence and reduces false identification of other sounds.
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
This approach effectively recognizes wind noise using existing earphone components, reducing hardware costs and enhancing recognition accuracy, even during active noise cancellation modes, and allows for subsequent wind noise suppression measures.
Implementation Method 1
a first microphone signal collected by a first microphone and a second microphone signal collected by a second microphone are acquired
Implementation Method 2
a wind noise recognition result of the earphone is obtained based on coherence between the first microphone signal and the first frequency domain filtered signal
Data Source
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AI summary
The disclosure discloses a method and apparatus for recognizing wind noise of an earphone. The earphone includes a first microphone located outside an ear and a second microphone located inside the ear. The method includes: a first microphone signal collected by the first microphone and a second microphone signal collected by the second microphone are acquired; a first frequency domain filtered signal is obtained based on the first microphone signal and the second microphone signal; and obtaining a wind noise recognition result of the earphone based on coherence between the first microphone signal and the first frequency domain filtered signal. According to the method for recognizing wind noise of an earphone of the embodiments of the disclosure, wind noise recognition is performed by using the existing first microphone located outside the ear and the existing second microphone located in the ear, other microphones are not needed to be set additionally, the hardware cost is reduced, and the effect of the wind noise recognition is good. The method for recognizing wind noise of an earphone is applicable to different wind noise recognition scenarios.