Audio Signal Encoding Using Partial Parameters and Entropy Coding
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Solution Overview
Problem
Current signal processing techniques for audio data transmission in complex communication environments are limited in maximizing transmission efficiency, particularly in achieving high-quality audio recovery with efficient data coding and decoding.
Innovation Solution
The method involves dividing audio signal parameters into partial parameters, using pilot reference values and difference values to optimize encoding and decoding, and employing entropy coding schemes like PBC and DIFF to enhance data compression and recovery efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional signal processing techniques are used for audio data transmission, then the transmission process is simple, but transmission efficiency cannot be maximized in complex communication environments
Solution Approach 1:
The patent divides audio signal parameters into partial parameters (first partial parameter and second partial parameter) for separate encoding and transmission. This segmentation allows optimized processing of different parameter components, improving transmission efficiency while managing complexity through structured organization of the processing scheme.
2Productivity
If high compression rates are achieved through signal processing techniques, then transmission efficiency improves, but audio or video quality may be compromised
Solution Approach 1:
The patent applies different processing approaches to different parts of the audio signal parameters. The first partial parameter is encoded using reference values and difference values, while the second partial parameter is handled separately. This local differentiation allows optimized compression for each parameter component while preserving the overall audio quality through selective processing.
3Productivity
If advanced coding schemes are implemented to maximize transmission efficiency, then data can be efficiently coded, but the complexity of encoding and decoding processes increases
Solution Approach 1:
The encoding process is segmented into distinct steps: obtaining reference values, calculating difference values, encoding the first partial parameter, and separately handling the second partial parameter. This structured segmentation improves data coding efficiency through systematic processing while managing encoding complexity through clear organization of the encoding workflow.
4Manufacturing precision
If control data for audio recovery is transmitted with high efficiency, then audio recovery quality improves, but the complexity of data structure and transfer protocols increases
Solution Approach 1:
The control data for audio recovery is segmented into different parameter components that are encoded and transmitted separately. The first partial parameter (encoded with reference and difference values) and second partial parameter are structured in a organized manner, improving audio recovery quality through precise data transmission while managing data structure complexity through systematic organization.
Data Source
AI summary
Apparatus and methods for processing a signal are disclosed. Data coding and entropy coding are performed with interconnection, and grouping is used to enhance coding efficiency. The subject matter includes a payload part having at least one of data coding information including pilot coding information per a frame and entropy coding information and a header part having main configuration information for the payload part.