Audio Encoder Bit Reallocation for Tonal Signal Precision
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Solution Overview
Problem
Modern audio encoders face challenges in accurately estimating bit consumption for audio signals, particularly for highly tonal signals, leading to inefficiencies and quality loss due to underestimation or overestimation of bit-consumption, which is exacerbated by the computational complexity of closed-loop iterations.
Innovation Solution
An audio encoder with a preprocessor and coder processor that adjusts the number of audio data items and information units based on signal characteristics, using a two-stage coding approach with an entropy encoder followed by a refinement stage, reallocating bits from the initial coding stage to the refinement stage for enhanced precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a power spectrum based estimator is used to estimate bit consumption, then encoding efficiency is improved for most audio content, but estimation accuracy deteriorates for highly tonal signals
Solution Approach 1:
The patent changes the estimation parameters by introducing a tonality detection mechanism that identifies highly tonal signals and switches to a different estimation approach. This allows the system to adapt the estimation parameters (power spectrum analysis vs. alternative method) based on the detected signal characteristics, thereby maintaining accuracy across different signal types while preserving encoding efficiency.
2Quantity of substance
If the number of audio data items is reduced for tonal signals, then bit consumption is optimized, but information loss increases
Solution Approach 1:
The patent applies local quality by differentiating processing strategies based on signal characteristics. For highly tonal signals, the system selectively reduces the number of audio data items after identifying tonal components, while preserving important tonal information through targeted encoding. This localized approach ensures that reduction is applied only where appropriate without causing unnecessary information loss.
Solution Approach 2:
The patent performs preliminary tonality detection and analysis before the actual encoding and reduction process. By identifying tonal signals in advance and estimating their bit consumption requirements beforehand, the system can make informed decisions about which data items to reduce and which to preserve, preventing information loss while achieving bit consumption optimization.
3Manufacturing precision
If closed-loop iteration is used to calculate optimal global gain, then encoding precision is improved, but computational complexity increases
Solution Approach 1:
The patent performs preliminary bit consumption estimation using power spectrum analysis and tonality detection before the actual encoding process. This preliminary action provides a good initial estimate of the optimal global gain, reducing or eliminating the need for computationally intensive closed-loop iterations while maintaining encoding precision.
Solution Approach 2:
The patent uses a simplified estimation model that copies the essential characteristics of the closed-loop iteration approach without implementing the full iterative process. By creating a lightweight estimation algorithm that replicates the key functionality of closed-loop optimization, the system achieves similar encoding precision with significantly reduced computational complexity.
Data Source
AI summary
An audio encoder for encoding audio input data has: a preprocessor for preprocessing the audio input data to obtain audio data to be coded; a coder processor for coding the audio data to be coded; and a controller for controlling the coder processor so that, depending on a first signal characteristic of a first frame of the audio data to be coded, a number of audio data items of the audio data to be coded by the coder processor for the first frame is reduced compared to a second signal characteristic of a second frame, and a first number of information units used for coding the reduced number of audio data items for the first frame is stronger enhanced compared to a second number of information units for the second frame.