Image-Adaptive Audio Processing for Voice and Noise Control
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Solution Overview
Problem
Existing audio signal processing devices fail to adapt their sound processing to the specific environment or situation, leading to inappropriate amplification or suppression of voices and noises in different spaces.
Innovation Solution
An audio signal processing device that uses image analysis to determine the environment (closed or open space) and adjusts acoustic parameters such as AGC and noise reduction accordingly, automatically setting parameters based on the estimated space type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automatic gain control is applied in all environments, then voice amplification is improved, but noise amplification worsens
Solution Approach 1:
The system dynamically adjusts the gain control strategy based on the detected environment type. In closed spaces, AGC is enabled to amplify voices, while in open spaces, AGC is disabled to avoid noise amplification. This dynamic adaptation resolves the contradiction by making the amplification behavior conditional rather than fixed.
Solution Approach 2:
The system changes the operational parameters of the audio processing pipeline based on environment detection. The gain control parameter is switched between different states (enabled/disabled) depending on whether the environment is classified as closed or open, allowing optimal performance for each scenario without compromise.
2Object-affected harmful factors
If noise suppression is applied in all environments, then noise reduction is improved, but voice quality worsens
Solution Approach 1:
The noise suppression functionality is dynamically enabled or disabled based on the detected environment. In open spaces where noise is prevalent, noise suppression is activated to reduce background noise. In closed spaces where voice quality is paramount, noise suppression is deactivated to preserve natural voice characteristics.
Solution Approach 2:
The system modifies the noise suppression parameter state according to environment type detection. This parameter switching allows the system to optimize for noise reduction in appropriate scenarios while maintaining voice quality in scenarios where it is more critical.
3Measurement precision
If manual parameter setting is required for different environments, then processing accuracy is improved, but ease of operation worsens
Solution Approach 1:
The system performs self-service by automatically detecting the environment type and configuring the appropriate audio processing parameters without user intervention. The environment detection module identifies whether the setting is closed or open space, and the control module automatically adjusts AGC and noise suppression settings accordingly, eliminating the need for manual parameter setting while maintaining high processing accuracy.
Solution Approach 2:
The system implements a feedback loop where the detected environment information is used to automatically adjust processing parameters. The environment detection result feeds into the parameter control mechanism, creating a closed-loop system that self-optimizes based on real-time conditions without requiring manual input from the user.
Data Source
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AI summary
The audio signal processing method in accordance with one embodiment receives an audio signal (SS1), obtains a first image (M1), estimates room information (RI) based on the obtained first image (M1), sets an acoustic parameter (SP) according to the estimated room information (RI), applies sound processing to the audio signal (SS1) according to the set acoustic parameter (SP), and outputs the audio signal (SS2) subjected to the sound processing.