Dynamic Audio Parameter Sharing for Real-Time Acoustic Filtering
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Solution Overview
Problem
Existing audio technologies fail to effectively allow listeners to customize their audio experience by attenuating or amplifying specific sound frequencies in real-time, while also providing privacy protection and adaptive noise management in various environments.
Innovation Solution
A sound processing system that includes personal audio systems with active acoustic filters and a sound knowledgebase, which use wireless communication to process ambient sound based on user preferences, location, and ambient sound profiles, allowing for real-time adjustment of audio streams and filtering parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If active acoustic filters are used to attenuate or amplify specific sound frequencies in real-time, then personalized audio experience is improved, but device complexity increases
Solution Approach 1:
The active acoustic filter system is designed to perform multiple audio processing functions including attenuation, amplification, noise reduction, and equalization across different frequency ranges. This multi-functionality allows a single device to provide personalized audio experiences for various listening scenarios (concerts, airplanes, sports events, construction sites) without requiring separate specialized devices for each function.
Solution Approach 2:
The system dynamically adjusts filter parameters in real-time based on ambient sound conditions and user preferences. The active acoustic filters can modify their characteristics on-the-fly to attenuate or amplify specific frequencies as needed, providing adaptive personalized audio experiences rather than static filtering configurations.
2Adaptability or versatility
If real-time audio processing is implemented to customize listening preferences, then audio quality is improved, but use of energy increases
Solution Approach 1:
The audio processing system operates in periodic cycles, analyzing ambient sound conditions and applying filter adjustments at appropriate intervals rather than continuously at maximum intensity. This periodic operation maintains high audio quality while reducing overall energy consumption compared to constant full-power processing.
Solution Approach 2:
The system applies partial processing to the audio signal by selectively filtering only the specific frequency ranges that require attenuation or amplification based on ambient conditions, rather than processing the entire audio spectrum uniformly. This targeted approach achieves the necessary audio quality improvement while consuming less energy than full-spectrum processing.
3Adaptability or versatility
If multiple processing parameters are adjusted based on location and ambient sound profiles, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system implements location-based and ambient sound profile-based processing by applying different filter parameters tailored to specific environments (e.g., concert venues, airplanes, sports events, construction sites). Each location or sound profile has optimized parameters for attenuating or amplifying frequencies relevant to that specific context, providing localized adaptability without requiring complete system redesign for each scenario.
Data Source
AI summary
Ambient sound is converted into an ambient audio stream. A processed ambient audio stream is generated by processing the ambient audio stream in accordance with a selected set of processing parameters selected from the plurality of processing parameter sets stored in the memory. Trigger data is searched and a new set of processing parameters is requested. The trigger data identifies the new set of processing parameters that is available for use in processing the ambient audio stream. A received new set of processing parameters is selected as the selected set of processing parameters. The processed ambient audio stream is converted into processed output sound.