Encoder Sub-band Amplitude Parameterization
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Solution Overview
Problem
Existing encoding apparatuses for broadband speech or sound signals face high computational complexity and inadequate quality in decoded signals due to applying calculated parameters uniformly across all samples without considering individual sample amplitudes, leading to inefficient arithmetic operations and potential abnormal sound generation.
Innovation Solution
The encoding apparatus calculates adjustment parameters based on sub-band energy and sample group positions with maximum amplitudes, applying these parameters only to the relevant sample groups, thereby reducing computational load and improving signal quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If parameters are calculated and applied to all samples within sub-bands uniformly, then the high-frequency spectrum can be generated, but the volume of arithmetic operations becomes very large
Solution Approach 1:
The patent applies different processing strategies to different regions within sub-bands. Specifically, it identifies samples with large amplitudes (above a threshold) and applies parameter adjustment only to these significant samples, while using different handling for smaller amplitude samples. This local differentiation reduces the number of arithmetic operations while maintaining spectrum generation accuracy where it matters most.
Solution Approach 2:
Instead of applying parameter calculations to all samples uniformly, the patent performs partial action by selectively applying adjustments only to samples that meet certain criteria (large amplitude samples). This partial approach sufficiently captures the essential spectral characteristics without the excessive computational cost of processing every sample, thereby improving arithmetic operation efficiency.
2Device complexity
If parameters are applied uniformly to all samples without considering individual sample amplitudes, then the encoding process is simplified, but the quality of decoded speech becomes insufficient and abnormal sound may be generated
Solution Approach 1:
The patent introduces local quality differentiation by examining individual sample amplitudes and applying different processing rules based on amplitude magnitude. Samples with large amplitudes receive specific parameter adjustments to preserve speech quality and avoid abnormal sounds, while other samples are handled differently. This localized approach maintains decoded speech quality without excessively complicating the overall encoding process.
Solution Approach 2:
The patent dynamically changes processing parameters based on sample characteristics. Specifically, it adjusts the application of scaling factors and parameter transformations based on whether samples exceed certain amplitude thresholds. This parameter adaptation ensures that critical speech components are preserved with high fidelity while maintaining reasonable encoding complexity.
3Loss of information
If logarithmic transform is applied to all MDCT coefficients, then the high-frequency spectrum data can be processed, but the volume of arithmetic operations increases significantly
Solution Approach 1:
The patent applies logarithmic transformation selectively rather than uniformly to all MDCT coefficients. It identifies regions and samples where logarithmic processing is most beneficial for preserving spectral information, and applies the transformation primarily in those areas. This localized application maintains essential spectrum information while significantly reducing the total volume of arithmetic operations compared to universal logarithmic transformation.
Data Source
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AI summary
Provided is an encoder which can effectively encode/decode spectrum data of a broad frequency signal in a high frequency range, can dramatically reduce the number of the arithmetic operations to be performed, and can improve the quality of the decoded signal. The encoder comprises a first layer coding unit (202) which encodes an input signal in a low frequency range below a predetermined frequency to generate first coded information, a first layer decoding unit (203) which decodes the first coded information to generate a decoded signal, and a second layer coding unit (206) which splits the input signal in a high frequency range above a predetermined frequency, into a plurality of sub-bands, presumes the respective sub-bands from the input signal or decoded signal, partially selects a spectrum component within each sub-band, and calculates an amplitude adjustment parameter used to adjust the amplitude of the selected spectrum component to thereby generate second coding information.