Audio Level Smoothing Using Time-Varying Probability Density
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Solution Overview
Problem
Existing audio signal processing methods, such as Automatic Gain Control (AGC), face challenges in adapting quickly to changes in audio signal levels, particularly when switching between channels or during dynamic content, leading to perceived volume fluctuations that can disrupt viewer experience.
Innovation Solution
The method involves estimating a time-varying probability density of the short-term audio signal level and using this estimate to dynamically adjust smoothing parameters, such as attack and release time constants, to ensure smooth adaptation to changing signal levels, preventing false switching between fast and slow smoothing modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If large time constants are used for smoothing the audio signal level, then the smoothed level varies slowly and maintains short-term dynamics, but the system takes a considerable amount of time to converge to new level after abrupt changes
Solution Approach 1:
The patent applies dynamics by making the smoothing parameters (time constants) variable rather than fixed. The system dynamically adjusts between fast and slow smoothing modes based on the detected state of the audio signal. When abrupt changes are detected, fast time constants are used for rapid convergence; when stability is needed, slow time constants are applied. This resolves the contradiction by allowing the system to have both quick response capability and stability at different times.
Solution Approach 2:
The patent changes the parameter of time constants from fixed values to variable values that adapt based on signal conditions. By monitoring the difference between short-term and smoothed levels, the system adjusts the smoothing parameter α to switch between fast and slow convergence modes. This parameter change enables the system to overcome the trade-off between convergence speed and stability.
2Speed
If fast time constants are used for smoothing, then the system quickly adapts to level changes, but the smoothed level may fluctuate excessively during typical signal dynamics
Solution Approach 1:
The system dynamically selects smoothing parameters based on real-time analysis of the audio signal characteristics. By continuously monitoring whether the short-term level difference from smoothed level exceeds a threshold, the system switches between fast and slow smoothing modes. This dynamic adaptation prevents excessive fluctuations during normal dynamics while enabling quick adaptation when needed.
Solution Approach 2:
The smoothing parameter α is changed from a fixed value to a variable parameter that adapts to signal conditions. When the signal exhibits typical dynamics, a slower smoothing parameter is used to prevent fluctuations. When abrupt changes occur, a faster parameter is applied for quick adaptation. This parameter adaptation resolves the contradiction between speed and stability.
3Speed
If threshold-based switching between fast and slow smoothing is implemented, then rapid adaptation during transitions is achieved, but false switching may occur during signals with large dynamics
Solution Approach 1:
The patent implements feedback by continuously monitoring the difference between short-term and smoothed levels and using this information to control the smoothing parameter selection. The system feeds back the current signal state to adjust the smoothing behavior, ensuring that mode switching occurs only when truly necessary. This feedback mechanism prevents false switching during signals with large but normal dynamics.
Solution Approach 2:
The system performs preliminary analysis of the signal characteristics before switching modes. By evaluating whether the level difference exceeds the threshold before committing to a mode change, the system avoids premature or false switching. This preliminary assessment ensures reliable mode selection based on actual signal conditions rather than transient fluctuations.
Data Source
AI summary
Methods, media and apparatus for smoothing a time-varying level of a signal. A method includes estimating a time-varying probability density of a short-term level of the signal and smoothing a level of the signal by using the probability density. The signal may be an audio signal. The short-term level and the smoothed level may be time series, each having current and previous time indices. Here, before the smoothing, computing a probability of the smoothed level at the previous time index may occur. Before the smoothing, calculating smoothing parameters using the probability density may occur. Calculating the smoothing parameters may include calculating the smoothing parameters using the smoothed level at the previous time index, the short-term level at the current time index and the probability of the smoothed level at the previous time index. Calculating the smoothing parameters may include calculating the smoothing parameters using breadth of the estimated probability density.