Selective De-reverberation via Blind Autocorrelation Estimation

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Solution Overview

Problem

Automatic speech recognition systems face challenges in processing utterances due to reverberation, which degrades recognition accuracy by interfering with sound reflections and environmental noise, and existing methods require prior knowledge of the environment or use pre-recorded test sounds, limiting adaptability to changing conditions.

Innovation Solution

The system employs blind estimation of reverberation levels in audio signals without prior knowledge of the environment, using autocorrelation analysis to estimate decay rates and determine the RT60 value, allowing for selective and adaptive de-reverberation to improve speech recognition accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If pre-recorded test sounds are used to determine reverberation level, then reverberation can be measured, but the system requires prior knowledge of the environment and cannot adapt to changing conditions

Engineering Contradiction:

Improvereverberation level measurementVSAvoidadaptability to changing acoustic conditions

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The system uses the actual speech signal itself to estimate reverberation characteristics through autocorrelation analysis, eliminating the need for external test sounds. The speech signal serves dual purposes: as the input to be processed and as the probe to characterize the acoustic environment, enabling continuous adaptation without requiring separate measurement phases.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary autocorrelation analysis on the speech signal to estimate decay rates and RT60 values before applying de-reverberation processing. This preliminary estimation enables the system to adaptively configure processing parameters based on the actual acoustic conditions present in the recorded signal.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If de-reverberation is applied to all audio signals, then speech recognition accuracy may improve in reverberant environments, but processing complexity increases and may degrade signals in low-reverberation conditions

Engineering Contradiction:

Improvespeech recognition accuracyVSAvoidprocessing complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system applies de-reverberation processing selectively based on the locally estimated reverberation characteristics of each audio signal. By using autocorrelation analysis to determine RT60 values for individual signals, the system tailors processing intensity to match actual reverberation levels, avoiding unnecessary processing in low-reverberation conditions while providing targeted enhancement where needed.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system dynamically adjusts de-reverberation processing based on real-time estimation of reverberation parameters from the speech signal itself. The processing characteristics change adaptively according to the measured decay rates and RT60 values, allowing the system to optimize performance across varying acoustic conditions rather than using fixed processing parameters.

Inventive Principle:

Principle #15Dynamics

3Adaptability or versatility

If blind estimation of reverberation is used without prior knowledge, then adaptability to changing conditions improves, but measurement precision may be affected by signal characteristics

Engineering Contradiction:

Improveadaptability to changing acoustic conditionsVSAvoidreverberation estimation accuracy

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The system estimates reverberation parameters (decay rates, RT60 values) directly from the speech signal by analyzing autocorrelation characteristics. By changing the approach from using external test sounds to extracting parameters from the signal itself, the system achieves continuous adaptation to varying acoustic conditions while maintaining measurement capability through mathematical analysis of the speech signal's temporal structure.

Inventive Principle:

Principle #35Parameter changes

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 enables automatic and adaptive de-reverberation, enhancing speech recognition performance by mitigating reverberation effects without the need for test sounds or environmental knowledge, and allows for real-time adjustments to changing acoustic conditions.

Implementation Method 1

using autocorrelation analysis to estimate decay rates and determine the RT60 value

Methodology Applied

Scientific EffectAutocorrelation:

Implementation Method 2

selective de-reverberation using blind estimation of reverberation level... mitigate reverberation effects

Methodology Applied

Scientific EffectReverberation: Reverberation

Data Source

PatentUS9558757B1Selective de-reverberation using blind estimation of reverberation level

Publication Date: 2017.01.31 AMAZON TECH INC

AI summary

Features are disclosed for estimating reverberation an audio signal without prior knowledge of the sound captured in the audio signal and without prior knowledge of the environment in which the sound was captured. This reverberation estimation may be referred to as “blind estimation.” The reverberation may be blindly estimated using autocorrelation of the sound intensity of the signal with respect to time. The blind estimation can be used to decide whether or not to mitigate the effects of reverberation in the signal prior to performing subsequent processes, such as automatic speech recognition.