Auditory Event Detection for Artifact-Free Dynamic Gain Control
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Solution Overview
Problem
Current audio dynamic range control methods are limited in effectively managing auditory events, leading to audible artifacts and inefficiencies in processing complex audio signals, as they fail to accurately detect and respond to changes in spectral content and perceived loudness.
Innovation Solution
The method involves performing auditory scene analysis by identifying auditory events through spectral analysis and transforming audio into a perceptual loudness domain, allowing for dynamic gain modification based on these events, thereby reducing audible artifacts and improving processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional audio dynamic range control methods are used, then processing is simpler, but audible artifacts increase and processing efficiency decreases
Solution Approach 1:
The audio signal is segmented into distinct auditory events using auditory scene analysis, which identifies separate sound sources and events within the mixed audio signal. This segmentation allows the system to apply different processing parameters to different events, improving accuracy while maintaining manageable complexity through event-based processing.
Solution Approach 2:
The system dynamically adjusts processing parameters based on the detected auditory events and their characteristics. The gain modification is not static but adapts in real-time to the detected events, allowing the system to handle complex audio scenarios with varying processing requirements without requiring overly complex fixed-structure processing.
2Measurement precision
If auditory event detection is implemented, then dynamic gain control accuracy improves, but computational demand increases
Solution Approach 1:
The system performs preliminary auditory scene analysis to detect and characterize events before applying gain modification. By identifying events and their boundaries in advance, the system avoids the need for complex real-time analysis during gain application, reducing overall computational energy requirements while maintaining high detection accuracy.
Solution Approach 2:
The patent introduces an intermediary processing stage that transforms audio into a perceptual loudness domain. This intermediary representation simplifies the detection of auditory events by mapping physical audio characteristics to perceptual attributes, reducing the computational complexity of event detection while improving accuracy in predicting human auditory perception.
Data Source
AI summary
In some embodiments, a method for processing an audio signal in an audio processing apparatus is disclosed. The method includes receiving an audio signal and a parameter, the parameter indicating a location of an auditory event boundary. An audio portion between consecutive auditory event boundaries constitutes an auditory event. The method further includes applying a modification to the audio signal based in part on an occurrence of the auditory event. The parameter may be generated by monitoring a characteristic of the audio signal and identifying a change in the characteristic.