Image-Based Audio Processing for Adaptive Gain and Noise Control
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Solution Overview
Problem
Existing audio signal processing devices fail to adapt sound processing to different usage situations, such as closed and open spaces, leading to inadequate amplification or noise suppression.
Innovation Solution
An audio signal processing method that estimates room information from an image, sets acoustic parameters accordingly, and applies sound processing to adjust gain control and noise reduction based on the estimated room type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If AGC amplifies the audio signal to enhance voice collection, then the voice signal quality is improved, but the background noise is also amplified
Solution Approach 1:
The patent dynamically changes the gain parameter based on the detected acoustic environment. In closed spaces, a higher gain is applied to amplify voice signals, while in open spaces, a lower gain is used to prevent noise amplification. This parameter adaptation resolves the contradiction by making the amplification level context-dependent rather than fixed.
Solution Approach 2:
The system transitions from static gain control to dynamic gain control by continuously detecting the acoustic environment and adjusting the amplification level accordingly. The gain parameter becomes a dynamic variable that adapts to changing spatial conditions, allowing the system to optimize voice collection while minimizing noise amplification in different environments.
2Object-affected harmful factors
If noise suppression is applied to reduce background noise, then the signal-to-noise ratio is improved, but the voice signal may be attenuated along with the noise
Solution Approach 1:
The noise suppression parameter is dynamically adjusted based on the acoustic environment detection. In closed spaces where noise levels are naturally lower, the noise suppression intensity is reduced to preserve voice signal strength. In open spaces with higher ambient noise, stronger noise suppression is applied. This parameter adaptation ensures that noise suppression effectiveness is optimized without causing excessive voice attenuation.
3Device complexity
If fixed acoustic parameters are used for sound processing, then the device complexity is reduced, but the adaptability to different environments is worsened
Solution Approach 1:
The system performs self-adaptation by automatically detecting the acoustic environment and adjusting its parameters without requiring manual user configuration. The device monitors spatial characteristics and autonomously optimizes gain and noise suppression parameters, eliminating the need for complex manual setup while achieving high environmental adaptability.
Solution Approach 2:
The system implements a feedback mechanism where the detected acoustic environment information is used to continuously adjust the sound processing parameters. The detection results feed back to the parameter control module, creating a closed-loop system that automatically adapts to different spatial conditions without user intervention, thereby achieving high versatility with minimal complexity.
Data Source
AI summary
The audio signal processing method in accordance with one embodiment receives an audio signal, obtains a first image, estimates room information based on the obtained first image, sets an acoustic parameter according to the estimated room information, applies sound processing to the audio signal according to the set acoustic parameter, and outputs the audio signal subjected to the sound processing.