Psychoacoustic Masking Thresholds for Dynamic Audio Bit Allocation

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Solution Overview

Problem

Existing audio encoding methods fail to accurately estimate masking thresholds based on known properties of human hearing, leading to inefficient bit allocation and reduced audio quality, particularly for signals with dynamic level changes.

Innovation Solution

A method for determining masking thresholds using energy values and hearing thresholds in quiet, combined with sensitivity values to calculate bit allocations that better reflect human hearing characteristics, thereby improving audio encoding accuracy and quality.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If traditional psychoacoustic models are used to estimate masking thresholds, then the encoding process can be simplified, but the accuracy of bit allocation and audio quality deteriorate

Engineering Contradiction:

Improveencoding process simplicityVSAvoidmasking threshold estimation accuracy

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent changes the parameters used in masking threshold estimation by incorporating sensation level (signal level relative to hearing threshold) and tonality measures into the calculation. This transforms the traditional fixed-parameter model into a dynamic model that adapts to different signal characteristics, thereby improving accuracy without significantly increasing complexity

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces complex heuristic rules with a more systematic approach based on known properties of human hearing (hearing threshold in quiet, critical bands, masking effects). This substitution of empirical heuristics with theory-based calculations improves measurement precision while maintaining computational efficiency

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Manufacturing precision

If more bits are allocated to frequency bands with lower masking thresholds, then audio quality improves, but bit allocation efficiency and compression ratio worsen

Engineering Contradiction:

Improveaudio qualityVSAvoidbit allocation efficiency

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The patent implements a feedback mechanism where the sensation level and tonality measures continuously inform the bit allocation decision. The system adjusts the masking threshold estimate based on the actual signal characteristics, creating a closed-loop control that optimizes bit allocation efficiency while maintaining audio quality

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent applies different bit allocation strategies to different frequency bands based on their local characteristics (sensation level and tonality). Rather than using a uniform allocation approach, the system tailors the bit allocation to the specific properties of each frequency band, improving both quality and efficiency

Inventive Principle:

Principle #3Local quality

3Device complexity

If heuristic rules are used for masking threshold determination, then the model complexity is reduced, but the reliability of the model based on human hearing properties deteriorates

Engineering Contradiction:

Improvemodel complexityVSAvoidmodel accuracy based on human hearing

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The patent replaces empirical heuristic rules with a model based on known properties of human hearing (hearing threshold in quiet, critical bands, masking effects). This substitution of empirical heuristics with theory-based calculations improves reliability while maintaining acceptable complexity through efficient algorithms

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20260024537A1Psychoacoustic model for audio processing

Publication Date: 2026.01.22 DOLBY LABORATORIES LICENSING CORP

AI summary

The present disclosure relates to the field of audio coding, in particular, it relates to a method for encoding audio signals through a masking model based on a hearing threshold of frequency intervals of the audio signal and a measured energy of the audio signal for the corresponding frequency intervals. The disclosure further relates to an encoder that is capable of carrying out the audio encoding method.