Vector Quantizer Multi-Stage Codebook Selection
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Solution Overview
Problem
In multi-stage vector quantization, the accuracy of quantization in second and later stages is insufficient due to the use of a single common codebook for varying types of narrowband LSPs, leading to degraded performance.
Innovation Solution
A vector quantization apparatus that selects a classification code vector indicating the type of feature correlated with the quantization target vector, uses a specific codebook and additive factor vectors to improve quantization accuracy by adapting to the type-specific distribution of quantization errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single common codebook is used in second and later stages of vector quantization, then the device complexity is reduced, but the quantization accuracy deteriorates
Solution Approach 1:
The patent applies local quality by using different codebooks for different types of narrowband LSPs in the second and later stages of vector quantization. Specifically, it classifies narrowband LSPs into multiple types based on their statistical characteristics, and assigns different codebooks to each type, allowing each codebook to be optimized for its specific LSP type rather than using a single common codebook for all types.
Solution Approach 2:
The patent changes the parameter of codebook selection based on the type of narrowband LSP. By identifying the LSP type in the first stage and using this information to select appropriate codebooks in subsequent stages, the system adapts the codebook parameters to match the statistical characteristics of the specific LSP type being processed, thereby improving quantization accuracy.
2Quantity of substance
If vector quantization is performed using 8 bits of information, then the amount of information transmission is reduced, but the codebook size must be limited to 256 vectors
Solution Approach 1:
The patent segments the vector quantization process into multiple stages: first-stage vector quantization that produces an initial quantized vector and error, followed by second-stage vector quantization of the error term. This segmentation allows the system to achieve better overall quantization accuracy than would be possible with a single 8-bit quantization, as the multi-stage process effectively increases the resolution without requiring a single large codebook.
Solution Approach 2:
The patent transitions from single-stage to multi-stage vector quantization, adding a temporal dimension to the quantization process. By performing quantization in multiple sequential stages rather than a single step, the system achieves higher effective resolution while maintaining the 8-bit information constraint, as each stage processes a different aspect of the quantization error.
Data Source
AI summary
Disclosed is a vector quantizer capable of improving the quantization accuracy of vector quantization to switch over the codebook of the vector quantization of a first stage depending on the type of feature having a correlation with a vector to be quantized. In the quantizer, a classifier (101) selects a classification code vector indicating the type of feature having the correlation with the vector to be quantized from a plurality of classification code vectors. A switch (102) selects a first codebook corresponding to the type from a plurality of first codebooks. An error minimizing section (105) selects a first code vector closest to the vector to be quantized from a plurality of first code vectors constituting the selected first codebook. An additivity factor determining section (106) selects an additivity factor vector corresponding to the type from a plurality of additivity factor vectors. The error minimizing section (105) selects a second code vector closest to the residual vector between the selected first code vector and the vector to be quantized from a plurality of second code vectors by using the selected additivity factor vector.