Frequency Envelope Vector Quantization With Segmented Codebooks
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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 using scalar quantization or traditional vector quantization methods.
Innovation Solution
A frequency envelope vector quantization method that divides frequency envelopes into multiple vectors with fewer dimensions, allowing for vector quantization using a codebook with a smaller number of bits, reducing complexity and ensuring quantization quality by adjusting the codebook based on the quantization result of the first vector.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If scalar quantization is used for each frequency envelope, then quantization precision can be maintained, but the quantity of bits consumed increases significantly
Solution Approach 1:
The patent combines multiple frequency envelopes into a single vector for joint quantization. Specifically, multiple frequency envelope values are merged into one vector object, which is then quantized using vector quantization techniques. This merging approach allows the system to maintain quantization precision while significantly reducing the total bit consumption compared to scalar quantization of each envelope separately.
2Measurement precision
If traditional vector quantization is used with a large codebook, then quantization quality can be improved, but the complexity of the system increases
Solution Approach 1:
The patent segments the codebook into multiple sub-codebooks, where each sub-codebook is dedicated to quantizing a specific vector. Instead of using one large codebook for all vectors, the system divides the codebook structure into smaller, manageable segments. This segmentation reduces the complexity of searching and managing the codebook while maintaining quantization quality, as each sub-codebook can be optimized for its specific vector type.
3Device complexity
If the codebook size is reduced to lower complexity, then system complexity decreases, but quantization precision deteriorates
Solution Approach 1:
The patent applies local quality by creating specialized sub-codebooks tailored to specific vector characteristics. Each sub-codebook is optimized for its particular vector type rather than using a generic, uniformly sized codebook. This allows the system to maintain high quantization precision for each specific vector type while keeping individual sub-codebooks smaller and less complex than a single large codebook would require.
Data Source
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AI summary
Embodiments of the present invention proposes a frequency envelope vector quantization method and apparatus, where the method comprises: dividing N frequency envelopes in one frame into N1 vectors, where each vector in the N1 vectors comprises M frequency envelopes; 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 parts; determining, according to the code word of the quantized first vector, that the quantized first vector is associated with the ith part in the 2B1 parts of the first codebook; determining a second codebook according to the codebook of the ith part; and quantizing a second vector in the N1 vectors based on the second codebook. In the embodiments of the present invention, frequency envelopes are divided into a plurality of vectors with fewer dimensions, so that 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.