Adaptive Signal Equalization for Noise Suppression Artifacts
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Solution Overview
Problem
Communication devices face reduced intelligibility due to detrimental side effects from noise suppression techniques, particularly high-frequency data attenuation, which affects audio quality and user experience.
Innovation Solution
The technology performs adaptive signal equalization based on noise suppression levels, using signal-to-noise ratio (SNR) or echo return loss (ERL) to counteract these effects, allowing for improved audio processing in both near-end and far-end signals, and across various noise types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise suppression techniques are applied to improve audio quality, then noise reduction is achieved, but high-frequency data attenuation occurs reducing signal intelligibility
Solution Approach 1:
The patent applies preliminary anti-action by performing equalization on the acoustic signal before noise suppression to pre-compensate for the high-frequency attenuation that will occur during noise suppression. This allows the signal to be restored to its original frequency balance after noise suppression, counteracting the detrimental side effects before they fully manifest.
Solution Approach 2:
The patent changes the equalization parameters dynamically based on the measured signal-to-noise ratio and the level of noise suppression applied. By adjusting equalization parameters in response to changing signal conditions, the system optimizes the balance between noise reduction and high-frequency preservation across different operating conditions.
2Reliability
If aggressive noise suppression is performed to improve signal clarity, then noise reduction increases, but signal intelligibility decreases due to high-frequency attenuation
Solution Approach 1:
The patent implements feedback by continuously monitoring the signal-to-noise ratio and the level of noise suppression applied, then using this information to dynamically adjust the equalization parameters. This closed-loop control ensures that the system maintains optimal signal intelligibility while achieving the desired noise reduction level.
Solution Approach 2:
The patent makes the equalization process dynamic by adapting the equalization parameters in real-time based on the current signal conditions and noise suppression level. This dynamic adjustment allows the system to respond to changing acoustic environments and maintain optimal performance across varying conditions.
3Loss of information
If equalization is applied to counteract noise suppression effects, then high-frequency restoration is achieved, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by performing equalization as a preprocessing step before noise suppression, rather than as a complex post-processing step. This approach simplifies the overall system architecture by preparing the signal in advance, reducing the need for complex adaptive algorithms during the main noise suppression process.
Data Source
AI summary
The present technology substantially reduces undesirable effects of multi-level noise suppression processing by applying an adaptive signal equalization. A noise suppression system may apply different levels of noise suppression based on the (user-perceived) signal-to-noise-ratio (SNR) or based on an estimated echo return loss (ERL). The resulting high-frequency data attenuation may be counteracted by adapting the signal equalization. The present technology may be applied in both transmit and receive paths of communication devices. Intelligibility may particularly be improved under varying noise conditions, e.g., when a mobile device user is moving in and out of noisy environments.