Content-Aware Noise Compensation for Timbre-Preserving Audio Playback
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Solution Overview
Problem
Existing noise compensation systems for audio devices often fail to effectively balance audio levels with environmental noise, particularly when playing music, leading to undesirable timbral shifts and listener dissatisfaction.
Innovation Solution
A noise compensation method that determines the content type, such as music or movie, to apply tailored noise compensation techniques, including frequency-dependent gains and constraints, to maintain the audio's timbre and adjust playback levels based on ambient noise and metadata, ensuring optimal audio reproduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise compensation is applied to audio playback, then audio intelligibility improves, but timbral accuracy deteriorates
Solution Approach 1:
The patent applies different noise compensation strategies to different frequency bands and content types. Music content receives timbre-preserving compensation with constrained gain adjustments, while dialogue content receives more aggressive noise suppression. This local differentiation resolves the contradiction by optimizing for intelligibility where needed while preserving timbre where important.
Solution Approach 2:
The system dynamically adjusts compensation parameters based on content type classification. For music, gain constraints and frequency weighting parameters are modified to preserve timbre, while for speech, parameters are optimized for intelligibility. This parameter adaptation allows the system to achieve both goals in their respective contexts.
2Measurement precision
If aggressive noise compensation is applied, then signal-to-noise ratio improves, but audio quality deteriorates
Solution Approach 1:
The patent implements content-type-specific compensation where music receives gentle, timbre-preserving processing while dialogue receives more aggressive noise suppression. This local quality approach ensures high SNR improvement for speech without degrading overall audio quality through excessive processing of all content.
Solution Approach 2:
The system applies noise compensation selectively based on content type rather than uniformly to all audio. For music, partial compensation is applied to maintain quality, while for dialogue, more aggressive compensation is used to improve SNR. This selective application resolves the contradiction by matching compensation intensity to content requirements.
3Device complexity
If uniform noise compensation is applied to all content types, then processing simplicity is maintained, but content-specific optimization is lost
Solution Approach 1:
The patent performs content type classification before applying noise compensation, allowing the system to select appropriate processing parameters in advance. This preliminary categorization enables content-specific optimization without requiring complex real-time adjustments, balancing simplicity and adaptability.
Solution Approach 2:
The system dynamically adapts compensation parameters based on detected content type, transitioning between different processing modes. This dynamic behavior allows the system to optimize for music or speech as needed while maintaining a relatively simple underlying processing architecture, resolving the contradiction between complexity and adaptability.
Data Source
AI summary
Some implementations involve receiving a content stream that includes audio data, determining a content type corresponding to the content stream and determining, based at least in part on the content type, a noise compensation method. Some examples involve performing the noise compensation method on the audio data to produce noise-compensated audio data, rendering the noise-compensated audio data for reproduction via a set of audio reproduction transducers of the audio environment, to produce rendered audio signals, and providing the rendered audio signals to at least some audio reproduction transducers of the audio environment.