Frequency Envelope Vector Quantization for Low-Bit Codebook Complexity
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Solution Overview
Problem
Existing frequency envelope quantization methods face challenges with insufficient quantization precision and excessive complexity due to limited bits in the codebook and a large number of frequency envelopes, particularly when scalar quantization is not suitable.
Innovation Solution
A frequency envelope vector quantization method that divides frequency envelopes into fewer-dimensional vectors, using a codebook with a smaller number of bits by dividing the initial codebook into portions, allowing for efficient quantization with reduced complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all frequency envelopes are combined as a single vector for vector quantization, then quantization precision is improved, but codebook size increases exponentially requiring more bits and increasing complexity
Solution Approach 1:
The patent divides N frequency envelopes into multiple sub-vectors instead of treating them as a single large vector. Each sub-vector contains fewer frequency envelopes, allowing the codebook to be segmented into corresponding portions. This reduces the dimensionality of each quantization task and prevents exponential growth of codebook size while maintaining comprehensive coverage of the frequency envelope space.
2Ease of manufacture
If scalar quantization is used for frequency envelopes, then implementation simplicity is improved, but bit consumption increases significantly when many frequency envelopes need to be quantized
Solution Approach 1:
The patent combines multiple frequency envelopes into vectors and applies vector quantization, merging the quantization process for multiple parameters into a single unified operation. This allows exploiting correlations between frequency envelopes to achieve more efficient representation, reducing total bit consumption compared to independent scalar quantization of each envelope.
3Measurement precision
If a large codebook is used to quantize all frequency envelopes together, then quantization quality is improved, but memory requirements and computational complexity increase
Solution Approach 1:
The patent segments both the frequency envelopes and the codebook into corresponding sub-vectors and codebook portions. This segmentation reduces the memory requirements for storing the codebook while maintaining quantization quality by ensuring that each sub-vector is quantized using an appropriately sized codebook portion that captures the essential characteristics of that subset of frequency envelopes.
Data Source
AI summary
Embodiments of the present application proposes a frequency envelope vector quantization method and apparatus, where the method includes: dividing N frequency envelopes in one frame into N1 vectors; quantizing a first vector in the N1 vectors by using a first codebook, to obtain a code word corresponding to the quantized first vector, where the first codebook is divided into 2B1 portions; determining, according to the code word corresponding to the quantized first vector; determining a second codebook according to the codebook of the ith portion; and quantizing a second vector in the N1 vectors based on the second codebook. In the embodiments of the present application, vector quantization can be performed on frequency envelope vectors by using a codebook with a smaller quantity of bits. Therefore, complexity of vector quantization can be reduced, and an effect of vector quantization can also be ensured.