Method and apparatus for multi-stage vector quantization for audio coding
By employing a segmented structure and multi-level vector quantization technology with optimized inner loop search, the problems of high storage space and search complexity in MSVQ are solved, achieving low-storage and low-complexity vector quantization and improving audio coding efficiency.
CN122290614APending Publication Date: 2026-06-26TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)
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Patent Information
- Application Number
- CN202610759130.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2023-03-23
- Filing Date
- 2024-02-14
- Publication Date
- 2026-06-26
AI Technical Summary
Technical Problem
Existing multi-level vector quantization (MSVQ) technology suffers from large storage space and high search complexity in audio coding, especially in EVS FD-CNG-VQ, where the ROM storage and WMOPS complexity of the first-level quantizer are relatively high.
Method used
The codebook design adopts a segmented structure. Through offline optimization and DCT transformation, the vector quantization is divided into multiple segments, each with a different truncation length. An optimized inner loop search and candidate update mechanism are used to reduce storage space and search complexity.
Benefits of technology
It effectively reduces storage space and search complexity, achieves low ROM and low WMOPS vector quantization, and improves coding efficiency.
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Abstract
Various embodiments of this disclosure disclose methods and apparatuses for multi-level vector quantization for audio coding. A method implemented by an encoder is disclosed. The method includes: obtaining a (1201) Discrete Cosine Transform (DCT) target vector; performing a (1203) suboptimal pairwise internal search in each segment of a codebook (104) having multiple segments to determine a set of pairwise initial candidates from each of the multiple segments, thereby forming a plurality of pairwise initial candidates from the suboptimal pairwise internal search, wherein each segment has a truncated vector different from the truncated vectors of the other segments in the plurality of segments, wherein the DCT target vector is the target of the suboptimal pairwise internal search for each of the multiple segments; reconstructing (1209) a plurality of final candidates using Inverse Type II Discrete Cosine Transform (DCT-II) to transform the plurality of final candidates into final candidate data in the original domain; and providing the final candidate data (1209) to a second stage of a multi-level vector quantizer.
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