Active Acoustic Filter for Annoyance Noise Suppression
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Solution Overview
Problem
Existing audio filtering technologies fail to effectively attenuate specific noise frequencies while allowing desirable sounds to pass through, particularly in environments with varying noise sources like concerts, airplanes, and construction sites, and they do not adapt well to user preferences or ambient noise characteristics.
Innovation Solution
A personal audio system with active acoustic filters that use a combination of band-reject filters and a sound knowledgebase to identify and suppress annoyance noise frequencies, while allowing desirable sounds to be heard, and can adapt filter settings based on user location and ambient noise profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If broad-spectrum noise cancellation is used to block out ambient noise, then annoyance noise is reduced, but desirable sounds such as speech and important environmental cues are also blocked
Solution Approach 1:
The system applies different filtering characteristics to different frequency ranges. Band-reject filters are configured to target specific annoyance noise frequencies (such as engine drone, air conditioner hum, or traffic noise) while preserving other frequency ranges where desirable sounds like speech and environmental cues are located. This localized frequency-specific filtering resolves the contradiction by selectively attenuating harmful frequencies without blocking useful auditory information.
Solution Approach 2:
The audio spectrum is segmented into multiple frequency bands, each processed independently with tailored filtering parameters. The system divides the broad frequency range into segments, applying aggressive noise cancellation only to segments containing annoyance noises while maintaining minimal processing in segments containing desirable sounds. This segmentation allows simultaneous noise reduction and information preservation across different spectral regions.
2Reliability
If fixed filter parameters are used to block specific frequencies, then annoyance noise suppression is effective for known noise sources, but the system cannot adapt to varying ambient noise characteristics in different environments
Solution Approach 1:
The filter parameters are made dynamic rather than fixed. The system continuously analyzes the ambient noise spectrum and automatically adjusts band-reject filter characteristics (center frequency, bandwidth, attenuation depth) in real-time based on detected noise sources. This dynamic adaptation allows the system to maintain effective noise suppression across varying environmental conditions, from quiet offices to noisy streets, resolving the contradiction between reliability and adaptability.
Solution Approach 2:
The system employs feedback mechanisms where the output of noise analysis feeds into filter parameter adjustment. Microphones capture ambient sound, spectral analysis identifies annoyance noise characteristics, and this information feeds back to modify filter settings accordingly. This closed-loop feedback system ensures reliable noise suppression while adapting to changing acoustic environments, as the filters continuously respond to actual measured noise conditions rather than relying on pre-programmed fixed parameters.
3Object-affected harmful factors
If aggressive noise filtering is applied to eliminate annoyance sounds, then hearing protection is improved, but the natural auditory experience and spatial awareness are degraded
Solution Approach 1:
The filtering is applied locally to specific frequency ranges rather than uniformly across the entire audio spectrum. Band-reject filters are configured with narrow bandwidths centered on annoyance noise frequencies, preserving the natural quality of other frequencies. This selective approach provides hearing protection from harmful noises while maintaining the natural auditory experience and spatial awareness dependent on preserved frequency content and ambient sound cues.
Data Source
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AI summary
Personal audio systems and methods are disclosed. A personal audio system includes a voice activity detector to determine whether or not an ambient audio stream contains voice activity, a pitch estimator to determine a frequency of a fundamental component of an annoyance noise contained in the ambient audio stream, and a filter bank to attenuate the fundamental component and at least one harmonic component of the annoyance noise to generate a personal audio stream. The filter bank implements a first filter function when the ambient audio stream does not contain voice activity, or a second filter function when the ambient audio stream contains voice activity.