Audio Noise Reduction via Frequency-Selective Estimation

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Solution Overview

Problem

Consumer electronic devices, such as Bluetooth headsets and wearable voice communication devices, face challenges in effectively reducing environmental noise during voice communications, especially when using multiple microphones, as they can be affected by physical aspects of the user's body and other phenomena, leading to poor separation between speech and ambient noises.

Innovation Solution

The use of a system that includes a first and second noise estimator, a selector, and an attenuator, which process audio signals from multiple microphones to generate noise estimates and apply attenuation based on frequency regions, allowing for improved noise reduction by selecting the appropriate noise estimate for each frequency region to minimize speech distortion.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Object-affected harmful factors

If two microphones are used to capture speech and ambient noise, then noise reduction capability is improved, but speech distortion increases due to physical aspects of user's body and acoustic phenomena

Engineering Contradiction:

Improveambient noiseVSAvoidspeech distortion

Core Design Contradiction:

Object-affected harmful factorsVSLoss of information

Solution Approach 1:

The frequency spectrum is divided into multiple frequency bins, allowing different noise estimation techniques to be applied to different frequency regions. This segmentation enables the system to process speech and noise separately in different frequency bands, reducing speech distortion while maintaining noise reduction effectiveness.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different noise estimation approaches (single-channel vs. two-channel) are selectively applied to different frequency bins based on their characteristics. The single-channel estimator is used for frequency bins where speech distortion is a concern, while the two-channel estimator is used where noise reduction is more critical, optimizing the balance between noise reduction and speech quality.

Inventive Principle:

Principle #3Local quality

2Loss of information

If single-channel noise estimation is used, then speech distortion is reduced, but noise reduction effectiveness decreases

Engineering Contradiction:

Improvespeech qualityVSAvoidambient noise

Core Design Contradiction:

Loss of informationVSObject-affected harmful factors

Solution Approach 1:

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system merges the results of single-channel and two-channel noise estimation by selecting the appropriate estimator output for each frequency bin. This combination allows the system to leverage the strengths of both approaches: speech quality preservation from single-channel estimation and noise reduction effectiveness from two-channel estimation.

Inventive Principle:

Principle #5Merging (Combining)

3Object-affected harmful factors

If two-channel noise estimation is used, then noise reduction effectiveness is improved, but speech distortion increases

Engineering Contradiction:

Improveambient noiseVSAvoidspeech distortion

Core Design Contradiction:

Object-affected harmful factorsVSLoss of information

Solution Approach 1:

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Inventive Principle:

Principle #3Local quality

4Device complexity

If uniform noise estimation is applied across all frequencies, then system complexity is reduced, but noise reduction performance deteriorates

Engineering Contradiction:

Improvenoise estimation systemVSAvoidambient noise

Core Design Contradiction:

Device complexityVSObject-affected harmful factors

Solution Approach 1:

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically selects between single-channel and two-channel noise estimation for each frequency bin based on signal characteristics. This dynamic adaptation allows the system to optimize noise reduction performance for each frequency region while managing overall system complexity through automated selection rather than manual configuration.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS10176823B2System and method for audio noise processing and noise reduction

Publication Date: 2019.01.08 APPLE INC

AI summary

Electronic system for audio noise processing and noise reduction comprises: first and second noise estimators, selector and attenuator. First noise estimator processes first audio signal from voice beamformer (VB) and generate first noise estimate. VB generates first audio signal by beamforming audio signals from first and second audio pick-up channels. Second noise estimator processes first and second audio signal from noise beamformer (NB), in parallel with first noise estimator and generates second noise estimate. NB generates second audio signal by beamforming audio signals from first and second audio pick-up channels. First and second audio signals include frequencies in first and second frequency regions. Selector's output noise estimate may be a) second noise estimate in the first frequency region, and b) first noise estimate in the second frequency region. Attenuator attenuates first audio signal in accordance with output noise estimate. Other embodiments are also described.