Audio Compression Coding Using Adaptive Absolute-Value Prediction
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Solution Overview
Problem
Conventional voice and audio compression methods are inefficient for signals with large dynamic ranges and rapid changes, as they fail to effectively predict and compress such signals, leading to poor compression efficiency.
Innovation Solution
The method involves extracting sign information from the input signal to obtain an absolute value signal, using prediction coefficients based on signal characteristics to calculate residual signals, and multiplexing these with sign information and coding parameters for entropy coding, thereby improving compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional prediction methods (LPC, LTP) are used for voice and audio compression, then compression efficiency is improved for signals with predictable patterns, but compression efficiency deteriorates for signals with large dynamic ranges and rapid changes
Solution Approach 1:
The patent applies dynamics by making the prediction method adaptive rather than fixed. The system dynamically selects between different prediction approaches (conventional LPC/LTP for predictable signals, alternative methods for signals with large dynamic ranges) based on the characteristics of the input signal, allowing the compression system to optimize performance for each specific signal type
Solution Approach 2:
The patent changes the parameters of the prediction system by introducing alternative prediction methods with different characteristics. Instead of using only fixed-order LPC and LTP predictors, the system employs multiple prediction approaches with varying parameters that can be selected based on signal properties, enabling effective compression of diverse signal types including those with rapid changes and large dynamic ranges
2Reliability
If lossless coding is used to ensure reconstructed signal consistency with original signal, then voice quality is ensured, but compression rate is reduced
Solution Approach 1:
The patent applies partial action by selectively applying different coding strategies to different parts of the signal or different signal components. Instead of uniformly applying lossless coding to all signals, the system uses lossless methods only when necessary (for signals where prediction residuals are difficult to compress) and allows lossy methods for other cases, achieving a balance between compression rate and reconstruction accuracy
Data Source
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AI summary
The embodiments of the present invention relate to a compression coding and decoding method, a coder, a decoder and a coding device. The compression coding method includes: extracting sign information of an input signal to obtain an absolute value signal of the input signal; obtaining a residual signal of the absolute value signal by using a prediction coefficient, where the prediction coefficient is obtained by prediction and analysis that are performed according to a signal characteristic of the absolute value signal of the input signal; and multiplexing the residual signal, the sign information and a coding parameter to output a coding code stream, after the residual signal, the sign information and the coding parameter are respectively coded, so as to improve compression efficiency of a voice and audio signal.