Acoustic Ambience Classification for Noise-Adaptive Device Operation
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Solution Overview
Problem
Existing systems face challenges in effectively modifying electronic device operations based on acoustic ambience, particularly in noisy environments, which can impact performance and user experience, such as in vehicles or homes, where background noise affects speech recognition and media playback.
Innovation Solution
An audio processing system that uses microphones and environmental sensors to classify ambient sounds, adjusting electronic device operations through a rules engine based on sound analysis, noise cancellation, and user input to enhance user interaction and system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automated speech recognition systems operate in noisy environments, then system accessibility and functionality are improved, but recognition accuracy deteriorates due to background noise
Solution Approach 1:
The system converts harmful background noise into useful information by analyzing acoustic characteristics to classify the environment. The noise cancellation module then uses this classification to selectively remove relevant noise components while preserving speech signals, transforming the harmful noise into a tool for improving recognition accuracy in noisy environments
Solution Approach 2:
The patent introduces an acoustic ambience classification module as an intermediary between the noisy environment and the speech recognition system. This module analyzes acoustic features and generates environment classifications that guide the noise cancellation process, serving as a mediator that enables the speech recognition system to adapt to different acoustic conditions without direct exposure to raw noise
2Productivity
If electronic systems continuously monitor and adapt to environmental conditions, then system performance and user experience are improved, but computational resource consumption and system complexity increase
Solution Approach 1:
The system segments the complex task of environmental adaptation into distinct modular components: an acoustic ambience classification module that analyzes and categorizes environmental sounds, a noise cancellation module that processes audio signals, and a rules engine that applies classification results to modify system operations. This segmentation reduces overall system complexity by making each component specialized and manageable
Solution Approach 2:
The acoustic ambience classification module performs preliminary analysis of the environment before the speech recognition or media playback operations begin. By pre-classifying the acoustic environment and identifying noise characteristics in advance, the system can apply appropriate noise cancellation strategies and adjustments without requiring complex real-time decision-making during critical operations
Data Source
AI summary
Methods and systems for modification of electronic system operation based on acoustic ambience classification are presented. In an example method, at least one audio signal present in a physical environment of a user is detected. The at least one audio signal is analyzed to extract at least one audio feature from the audio signal. The audio signal is classified based on the audio feature to produce at least one classification of the audio signal. Operation of an electronic system interacting with the user in the physical environment is modified based on the classification of the audio signal.