Real-Time Volume Leveler Control for Artifact-Free Audio Transitions
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Solution Overview
Problem
Traditional audio processing systems require manual preset selection for different audio content types, leading to inconvenient user experiences and audible artifacts during transitions, as they lack continuous adjustment capabilities based on real-time content identification.
Innovation Solution
An audio processing apparatus and method that automatically classify audio signals in real-time and adjust parameters of devices like dialog enhancers, surround virtualizers, and equalizers in a continuous manner using an audio classifier and adjusting unit, based on confidence values to identify and respond to different audio types and contexts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual preset selection is used for different audio content types, then the system can apply appropriate processing algorithms, but the user experience becomes inconvenient and audible artifacts occur during transitions
Solution Approach 1:
The system dynamically adjusts audio processing parameters in real-time based on continuous audio content classification, transitioning smoothly between different content types (music, speech, noise) without requiring manual preset changes. This dynamic adaptation eliminates abrupt transitions and audible artifacts while maintaining optimal processing for each content type.
Solution Approach 2:
The system continuously monitors and classifies audio content in real-time, using the classification results to automatically adjust processing parameters. This closed-loop feedback mechanism ensures the system responds adaptively to changing audio content, maintaining high quality without user intervention and avoiding artifacts during content transitions.
2Device complexity
If discrete parameters are used in presets for different audio types, then the system can be simplified, but continuous adjustment capability is lost leading to audible artifacts
Solution Approach 1:
The system replaces discrete preset parameters with continuous dynamic parameter adjustment based on real-time audio classification. By continuously adapting parameters according to the classified audio content type and confidence level, the system eliminates abrupt parameter switches that cause audible artifacts while maintaining manageable system complexity through automated control.
Solution Approach 2:
The system changes processing parameters continuously based on audio content classification results and confidence values, rather than switching between fixed discrete presets. This continuous parameter adaptation allows smooth transitions between different audio content types, eliminating audible artifacts while keeping the system structure relatively simple through automated parameter management.
3Extent of automation
If automatic audio classification is implemented in real-time, then continuous parameter adjustment is enabled, but system complexity increases
Solution Approach 1:
The system performs automatic audio content classification and parameter adjustment without requiring external control or user intervention. The classification module autonomously identifies audio content types and confidence levels, and the processing parameters are automatically adapted based on these classifications, enabling high automation while managing complexity through integrated self-control mechanisms.
Solution Approach 2:
The audio classification and parameter adjustment system serves multiple functions: it classifies audio content types, determines confidence levels, selects appropriate processing algorithms, and continuously adjusts parameters. By consolidating these functions into an integrated automated system, the patent achieves high extent of automation while managing overall system complexity through functional consolidation.
Data Source
AI summary
Volume leveler controller and controlling method are disclosed. In one embodiment, A volume leveler controller includes an audio content classifier for identifying the content type of an audio signal in real time; and an adjusting unit for adjusting a volume leveler in a continuous manner based on the content type as identified. The adjusting unit may configured to positively correlate the dynamic gain of the volume leveler with informative content types of the audio signal, and negatively correlate the dynamic gain of the volume leveler with interfering content types of the audio signal.