Audio Perception Intensity Evaluation for Automatic Gain Control
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Solution Overview
Problem
Current methods for loudness estimation of audio signals are complex and processing-intensive, particularly when differentiating between speech and other audio components, making them unsuitable for automated gain control applications.
Innovation Solution
A method that estimates perception intensity using a time variant distribution function, allowing for universal and flexible evaluation of audio signals, including speech, music, and noise, through feed-forward or feed-back implementations, and non-linear signal processing, enabling automatic gain control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated loudness estimation is implemented, then productivity is improved, but measurement precision deteriorates due to inability to capture subjective perception accurately
Solution Approach 1:
The patent transforms the loudness estimation problem by changing parameters from traditional energy-based measurements to perceptual parameters including temporal envelope characteristics, spectral distribution, and psychoacoustic masking effects. This allows automated systems to better predict human perception by using parameters that reflect how the human ear actually processes sound.
Solution Approach 2:
The patent introduces intermediate processing stages including temporal envelope extraction, spectral analysis, and psychoacoustic model application between the raw audio signal and final loudness measurement. These intermediaries translate physical sound properties into perceptual equivalents that better match human hearing characteristics.
2Measurement precision
If speech components are separated and processed differently, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the audio signal processing into distinct functional blocks: temporal envelope extraction, spectral analysis, psychoacoustic model application, and loudness calculation. This segmentation allows speech and non-speech components to be processed through the same structured pipeline, maintaining precision while managing complexity through modular design.
Solution Approach 2:
The patent creates a universal processing framework that handles both speech and non-speech signals through the same temporal envelope and spectral analysis mechanisms. The system adapts to different signal types without requiring separate dedicated processing paths, reducing overall system complexity while maintaining accuracy for speech components.
3Measurement precision
If manual subjective analysis is used, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces manual subjective analysis with an automated computational system that uses psychoacoustic models and signal processing algorithms to predict human perception. This substitution maintains measurement precision by incorporating perceptual psychology principles while dramatically increasing productivity through automated computation.
Solution Approach 2:
The patent creates a computational model that copies and simulates human auditory perception mechanisms. By replicating the physiological and psychological aspects of hearing in software, the system achieves subjective assessment accuracy without requiring actual human listeners, thereby enabling high-speed automated processing.
4Adaptability or versatility
If a universal loudness evaluation method is implemented, then adaptability is improved, but measurement precision deteriorates for specific signal types
Solution Approach 1:
The patent implements a dynamic universal evaluation method that automatically adapts its processing parameters based on the characteristics of the input signal. The system analyzes temporal envelope patterns, spectral distribution, and signal statistics to dynamically adjust processing gains and parameters, maintaining high precision across different signal types including speech, music, and noise without requiring manual configuration.
Data Source
AI summary
Method of evaluating perception intensity of an audio input signal (IS) comprising the steps of receiving the audio input signal (IS), estimating a time variant distribution function (TVDF) on the basis of said audio input signal (IS) or a derivative thereof, determining the perception intensity as at least one perception intensity estimate (PIE) on the basis of said estimated time variant distribution function (TVDF). According to the invention perception intensity has been obtained on the basis of a time variant distribution function. Thereby, an advantageous universal and flexible determination of perception intensity is obtained. The universal applicability is basically obtained due to the fact that a distribution function may match and describe audio input signal of very different nature. Thus, according to the invention even speech, music and noise may be evaluated on the basis of a distribution function.