Multi-Channel Audio Encoding With Transient-Aware Block Grouping
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Solution Overview
Problem
Current audio data compression technologies suffer from low encoding quality and poor reconstruction effects, particularly for transient signals in multi-channel audio signals.
Innovation Solution
A method that groups and adjusts block information based on transient identifiers to improve encoding quality, using a neural network for encoding and decoding, and prioritizes transient features in the encoding process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional audio data compression technology is used, then data transmission and storage are facilitated, but encoding quality and reconstruction effect deteriorate for transient signals
Solution Approach 1:
The audio signal is divided into multiple frames, with each frame containing multiple blocks. Transient identifiers are generated for each block to distinguish transient blocks from non-transient blocks, enabling differentiated processing that improves encoding quality for transient signals while maintaining manageable system complexity through structured segmentation
Solution Approach 2:
Different encoding strategies are applied to transient blocks and non-transient blocks based on their respective transient identifiers. Transient blocks undergo specific processing tailored to their characteristics, while non-transient blocks use standard processing, thereby improving overall encoding quality without uniformly increasing complexity across all signal portions
2Reliability
If multi-channel audio signals are compressed, then data amount is reduced, but reconstruction effect deteriorates
Solution Approach 1:
Transient identifiers are generated in advance during the encoding process to mark transient blocks before compression. This preliminary identification enables the decoder to reconstruct transient blocks with appropriate processing, improving reconstruction effect while maintaining data compression efficiency
Solution Approach 2:
The transient identifiers are embedded in the bitstream and fed back to the decoder, which uses this information to guide the reconstruction process. This feedback mechanism ensures that transient blocks are reconstructed with higher fidelity, improving overall reconstruction effect while maintaining efficient data compression
Data Source
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AI summary
Disclosed are a multi-channel signal encoding and decoding method and apparatus. In a multi-channel signal encoding method, a current frame of a to-be-encoded multi-channel signal includes a first sound channel and a second sound channel. First group information of M blocks of the first sound channel and second group information of M blocks of the second sound channel are obtained. When the first group information and the second group information meet a preset condition, first adjusted group information and second adjusted group information are obtained based on the first group information and the second group information (405). Then, a first to-be-encoded spectrum is obtained based on the first adjusted group information and the spectrums of the M blocks of the first sound channel (406). Similarly, a second to-be-encoded spectrum may be obtained (407). Finally, the first to-be-encoded spectrum and the second to-be-encoded spectrum are encoded by using an encoding neural network, to obtain a spectrum encoding result (408). The spectrum encoding result may be carried by a bitstream (409). Blocks with different transient identifiers can be grouped, adjusted, and encoded. This improves encoding quality of the multi-channel signal.