Adaptive Blocking Matrix Noise Correlation Tracking

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Solution Overview

Problem

Conventional adaptive beamformers may unintentionally remove noise correlation, leading to uncorrelated noise remaining in the signal, which cannot be effectively canceled, resulting in residual noise in the processed signal.

Innovation Solution

Modifying the adaptive filter to track and maintain noise correlation between microphone signals by determining a noise correlation factor and using it to derive the correct inter-sensor signal model, with the option of applying spatial pre-whitening in the adaptive blocking matrix to enhance noise reduction, employing algorithms like gradient descent total least squares (GrTLS) for improved noise reduction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Object-affected harmful factors

If an adaptive blocking matrix is used to reduce noise in adaptive beamforming, then noise reduction performance is improved, but noise correlation is unintentionally removed causing residual uncorrelated noise to remain

Engineering Contradiction:
Improvenoise reduction performanceVSAvoidnoise correlation maintenance
Core Design Contradiction:
Object-affected harmful factorsVSReliability

Solution Approach 1:

The patent implements feedback by calculating the actual noise correlation from microphone signals and using it to adjust the adaptive blocking matrix parameters. The noise correlation calculation unit continuously monitors the correlation between noise components in different microphone signals and feeds this information back to the adaptive blocking matrix to maintain optimal noise reduction while preserving correlation.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The patent dynamically changes parameters of the adaptive blocking matrix based on the calculated noise correlation. By adjusting the blocking matrix parameters according to the measured noise correlation level, the system adapts to maintain the desired balance between noise reduction and correlation preservation, preventing the loss of useful noise correlation.

Inventive Principle:
Principle #35Parameter changes

2Measurement precision

If the adaptive filter processes signals to reduce noise, then signal quality is improved, but noise correlation is lost leading to uncorrelated noise that cannot be canceled

Engineering Contradiction:
Improvesignal qualityVSAvoidnoise correlation
Core Design Contradiction:
Measurement precisionVSLoss of information

Solution Approach 1:

The patent performs preliminary action by calculating the noise correlation before the adaptive filter processes the signals. By determining the noise correlation in advance and using it to configure the adaptive blocking matrix, the system prepares the processing chain to preserve correlation while still achieving noise reduction through subsequent adaptive filtering.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary element - the noise correlation calculation unit and its output - that mediates between the raw microphone signals and the adaptive filter. This intermediary calculates the correlation metric and uses it to adjust the blocking matrix, thereby protecting the noise correlation information from being lost during adaptive filtering while still enabling noise reduction.

Inventive Principle:
Principle #24Intermediary (Mediator)

Data Source

PatentEP3357256B1Apparatus using an adaptive blocking matrix for reducing background noise
Publication Date: 2022.03.30 CIRRUS LOGIC INT SEMICON LTD
  • EP3357256B1 patent drawingFigure 1
  • EP3357256B1 patent drawingFigure 2
  • EP3357256B1 patent drawingFigure 3

AI summary

An adaptive filter of an adaptive blocking matrix in an adaptive beam former or null former may be modified to track and maintain noise correlation between an input and a reference noise signal to the adaptive noise canceller module. That is, a noise correlation factor may be determined, and that noise correlation factor may be used in an inter-sensor signal model applied when generating the blocking matrix output signal. The output signal may then be further processed within the adaptive beamformer to generate a less-noisy representation of the speech signal received at the microphones. The inter-sensor signal model may be estimated using a gradient decent total least squares (GrTLS) algorithm. Further, spatial pre-whitening may be applied in the adaptive blocking matrix to further improve noise reduction.