Vector Joint Encoding Index Segmentation for Speech Signal Processing
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Solution Overview
Problem
In vector encoding, existing methods like AMR_WB+ suffer from high calculation complexity and redundancy in encoding indices, leading to inefficient use of bits, especially when encoding a large number of pulses, resulting in wasted encoding bits and increased processing complexity.
Innovation Solution
The method involves jointly encoding multiple vectors, splitting and recombining their encoding indices to reduce bit requirements, allowing for more efficient use of encoding bits and reducing the length of data needed for calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple vectors are jointly encoded using existing methods (e.g., AMR_WB+), then encoding can be performed, but calculation complexity increases and encoding bits are wasted due to redundancy in encoding indices
Solution Approach 1:
The patent divides the encoding index of each vector into multiple segments (first encoding index and second encoding index). This segmentation allows the most significant bits to be encoded jointly across vectors while less significant bits are encoded independently, reducing redundancy and calculation complexity while maintaining encoding efficiency.
Solution Approach 2:
The patent merges the encoding of multiple vectors by jointly encoding the first encoding indices of all vectors together. This combining approach exploits the redundancy among vectors and allows efficient use of encoding bits, reducing the total number of bits needed compared to encoding each vector separately.
2Loss of substance
If encoding indices are encoded separately for each vector, then encoding is simple, but redundancy accumulates and encoding bits are wasted
Solution Approach 1:
The encoding index is segmented into two parts: a first encoding index containing the most significant bits that are jointly encoded across vectors, and a second encoding index containing less significant bits that are encoded independently. This segmentation reduces redundancy while maintaining manageable complexity.
Solution Approach 2:
Different parts of the encoding index have different encoding strategies. The first encoding index uses joint encoding to reduce redundancy across vectors, while the second encoding index uses independent encoding for simplicity. This local differentiation optimizes the balance between reducing bit waste and maintaining structural simplicity.
3Quantity of substance
If the number of pulses encoded on each track increases, then encoding capacity improves, but redundancy in encoding indices increases leading to wasted bits
Solution Approach 1:
The encoding index is segmented into significant and less significant portions. The first encoding index captures the most significant information that varies across pulses and is jointly encoded, while the second encoding index handles the less significant portions independently. This reduces redundancy as the number of pulses increases.
Solution Approach 2:
The patent introduces a new dimension to the encoding structure by separating the encoding index into two parts with different encoding strategies. This dimensional change allows the system to handle increasing numbers of pulses efficiently by exploiting the structure of the encoding index rather than treating all bits uniformly.
Data Source
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AI summary
A vector joint encoding/decoding method and a vector joint encoder/decoder are provided, more than two vectors are jointly encoded, and an encoding index of at least one vector is split and then combined between different vectors, so that encoding idle spaces of different vectors can be recombined, thereby facilitating saving of encoding bits, and because an encoding index of a vector is split and then shorter split indexes are recombined, thereby facilitating reduction of requirements for the bit width of operating parts in encoding/decoding calculation.