Adaptive Sinusoidal Audio Coding for Energy-Based Bit Allocation
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Solution Overview
Problem
Existing audio signal encoding and decoding technologies face challenges in efficiently improving the quality of synthesized signals, particularly when the number of bits available for sinusoidal coding is insufficient, as they often apply coding uniformly across all frequency bands without considering the varying energy distribution of signals.
Innovation Solution
The method involves dividing audio signals into sub-bands, calculating their energy, and selectively applying sinusoidal coding to sub-bands with the largest energy, ensuring that bits are allocated based on the significance of each sub-band's influence on the signal quality, thereby improving the quality of synthesized signals efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If sinusoidal coding is applied uniformly across all frequency bands, then the coding process is simple, but the quality of synthesized signals is not efficiently improved when bits are insufficient
Solution Approach 1:
The patent applies sinusoidal coding selectively to specific frequency sub-bands rather than uniformly across all bands. The encoder divides the frequency spectrum into multiple sub-bands and identifies those with higher energy content, then applies sinusoidal coding preferentially to these high-energy sub-bands. This localized approach ensures that limited coding bits are allocated to the most perceptually important regions, thereby improving synthesized signal quality without requiring uniform complex processing across the entire spectrum.
Solution Approach 2:
The patent dynamically adjusts coding parameters based on the energy distribution across different frequency sub-bands. By calculating the energy of each sub-band and using this information to determine where to apply sinusoidal coding, the system adapts its coding strategy to match the actual signal characteristics. This parameter adaptation allows efficient use of limited bits while maintaining or improving signal quality.
2Manufacturing precision
If the number of bits for sinusoidal coding is increased, then the quality of synthesized signals improves, but the bitrate increases
Solution Approach 1:
Instead of increasing the overall bitrate, the patent concentrates coding resources on specific high-energy sub-bands where they will have the greatest impact on perceived quality. By dividing the frequency spectrum and selectively applying sinusoidal coding only to sub-bands with significant energy content, the system achieves better synthesized signal quality without proportionally increasing the total number of bits required.
Solution Approach 2:
The patent applies sinusoidal coding to only the most important sub-bands (those with highest energy) rather than attempting to code all sub-bands equally. This partial action approach focuses computational and bit resources on the critical regions that contribute most to signal quality, achieving effective quality improvement with limited bit allocation.
3Adaptability or versatility
If sinusoidal coding is applied to all sub-bands with limited bits, then bit allocation is uniform, but the influence of energy distribution on signal quality is ignored
Solution Approach 1:
The patent replaces uniform bit allocation with adaptive allocation based on local energy characteristics of each sub-band. By calculating the energy of individual sub-bands and using this information to guide where sinusoidal coding is applied, the system ensures that bits are allocated to regions where they will have maximum impact on signal quality, rather than distributing them uniformly regardless of local signal characteristics.
Solution Approach 2:
The bit allocation strategy is made dynamic by baseing it on the actual energy distribution in the input signal. The encoder calculates sub-band energies and adapts its coding decisions accordingly, allowing the system to respond to varying signal characteristics in different time frames and frequency regions. This dynamic adaptation optimizes the use of limited bits to match the actual signal content.
Data Source
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AI summary
A method and an apparatus for encoding and decoding audio signals using adaptive sinusoidal coding are provided. The audio signal encoding method includes the steps of dividing a synthesized audio signal into a plurality of sub-bands, calculating the energy of each sub-band, selecting a predetermined number of sub-bands having a relatively large amount of energy from the sub-bands, and performing sinusoidal coding with regard to the selected sub-bands. Application of sinusoidal coding based on consideration of the amount of energy of each sub-band of the synthesized signal improves the quality of the synthesized signal more efficiently.