Wearable Listen-Through Audio With Self-Voice Signal Separation
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Solution Overview
Problem
Wearable devices face challenges in providing a natural listen-through experience due to the inability to seamlessly distinguish and process self-voice signals and external signals, which results in distorted audio input when both types of signals have different distortion patterns.
Innovation Solution
The implementation of beamforming operations and separate filtering procedures to isolate and process self-voice signals and external signals separately, applying a first filter to the external signal and a second filter to the self-voice signal, and then mixing them to generate an output signal that sounds natural to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single filtering procedure is applied to all audio signals, then the device complexity is reduced, but the audio quality and naturalness deteriorate due to inability to handle different distortion patterns
Solution Approach 1:
The patent segments the audio signal processing by separating self-voice signals from external signals through beamforming, then applying different filtering procedures to each segment. This allows tailored processing for each signal type, improving audio quality while maintaining manageable complexity through modular processing stages.
Solution Approach 2:
The patent applies the principle of local quality by using different filtering characteristics for different signal sources. Self-voice signals receive one type of filtering while external signals receive another, ensuring each signal type is processed with the appropriate filter characteristics for its specific distortion pattern.
2Manufacturing precision
If beamforming and separate filtering procedures are implemented, then the audio quality and naturalness are improved, but the device complexity increases
Solution Approach 1:
The complex processing is broken into distinct segments: beamforming for signal separation, followed by separate filtering stages for self-voice and external signals. This segmentation makes the overall complex system more manageable and implementable through modular processing blocks.
Solution Approach 2:
The patent performs preliminary beamforming operations to separate signals before applying filtering. This preliminary separation action simplifies subsequent processing by pre-organizing the signal components, making the overall complex processing more efficient and implementable.
3Speed
If self-voice and external signals are processed together, then the processing speed is maintained, but the audio naturalness deteriorates due to different distortion patterns
Solution Approach 1:
The patent segments signals into self-voice and external components through beamforming, then processes each segment with appropriate filtering. This segmentation enables parallel or sequential processing that maintains speed while achieving natural output through source-specific filtering.
Solution Approach 2:
The patent changes processing parameters based on signal type, applying different filter characteristics to self-voice versus external signals. This parameter adaptation allows optimized processing for each signal type, maintaining speed while improving naturalness through appropriate filtering selection.
Data Source
AI summary
Methods, systems, and devices for signal processing are described. Generally, as provided for by the described techniques, a wearable device may receive an input audio signal (e.g., including both an external signal and a self-voice signal). The wearable device may detect the self-voice signal in the input audio signal based on a self-voice activity detection (SVAD) procedure, and may implement the described techniques based thereon. The wearable device may perform beamforming operations or other separation procedures to isolate the external signal and the self-voice signal from the input audio signal. The wearable device may apply a first filter to the external signal, and a second filter to the self-voice signal. The wearable device may then mix the filtered signals, and generate an output signal that sounds natural to the user.