Multi-Microphone Dereverberation via Signal Correlation Analysis
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Solution Overview
Problem
Existing audio processing systems face challenges in accurately reducing reverberation in diverse and dynamic acoustic environments, leading to residual distortion and interference in electrical signals during teleconferencing and hands-free communication.
Innovation Solution
A multi-faceted analysis using acoustic signals from multiple microphones to determine the correlation between signals, identifying reverberation components, and applying signal modifications to reduce their energy levels, thereby preserving speech and minimizing reverberation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If transfer function based deconvolution is used for dereverberation, then reverberation reduction is achieved, but residual reverberation and distortion remain due to inaccurate environmental modeling
Solution Approach 1:
The patent introduces an intermediary approach by using multiple acoustic signals from different microphones as mediators to characterize the acoustic environment, rather than relying directly on a single transfer function. These multiple signals serve as intermediate representations that capture environmental properties more robustly, enabling better dereverberation without the residual distortion problems of traditional methods
Solution Approach 2:
The patent changes the parameters used to model the acoustic environment from a single transfer function to multiple acoustic signals with varying characteristics. By analyzing correlations across multiple signals with different spatial and temporal properties, the system achieves more accurate environmental characterization and consequently better dereverberation performance
2Device complexity
If single microphone signal processing is used, then processing complexity is low, but accurate separation of speech from reverberation is difficult
Solution Approach 1:
The patent merges multiple acoustic signals from different microphones into a unified analysis framework. By combining these signals and analyzing their correlations, the system achieves accurate speech-reverberation separation that would be impossible with a single microphone, while maintaining computational efficiency through shared processing components
3Adaptability or versatility
If transfer function modeling is used to estimate acoustic environment, then dereverberation can be performed, but errors occur when acoustic environment is dynamic and changing
Solution Approach 1:
The patent implements a dynamic approach by continuously analyzing multiple acoustic signals to adaptively characterize the acoustic environment. Rather than relying on a fixed transfer function, the system dynamically updates its environmental model based on correlations observed across multiple signals, enabling accurate dereverberation even when the acoustic environment changes over time
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 provides robust and high-quality dereverberation, effectively distinguishing between speech and reverberation, resulting in improved intelligibility and reduced distortion in acoustic signals across various environments.
Implementation Method 1
determine the correlation between the acoustic signals. Due to the spatial distance between the microphones and the variation in reflection paths present in the surrounding acoustic environment, the correlation between the acoustic signals can be used to accurately determine whether portions of one or more of the acoustic signals contain desired speech or undesired reverberation
Data Source
AI summary
The present technology provides robust, high quality dereverberation of an acoustic signal which can overcome or substantially alleviate the problems associated with the diverse and dynamic nature of the surrounding acoustic environment. The present technology utilizes acoustic signals received from a plurality of microphones to carry out a multi-faceted analysis which accurately identifies reverberation based on the correlation between the acoustic signals. Due to the spatial distance between the microphones and the variation in reflection paths present in the surrounding acoustic environment, the correlation between the acoustic signals can be used to accurately determine whether portions of one or more of the acoustic signals contain desired speech or undesired reverberation. These correlation characteristics are then used to generate signal modifications applied to one or more of the received acoustic signals to preserve speech and reduce reverberation.