Adaptive Sinusoidal Audio Coding for Energy-Based Sub-Band Selection
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Solution Overview
Problem
Existing audio signal encoding and decoding technologies face challenges in improving the quality of synthesized signals, particularly when bit allocation is limited, as they often apply sinusoidal coding uniformly across all sub-bands without considering energy distribution.
Innovation Solution
The method involves dividing audio signals into sub-bands, calculating the energy of each sub-band, and selectively applying sinusoidal coding to those sub-bands with the largest energy, thereby optimizing bit usage and enhancing signal quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If sinusoidal coding is applied uniformly to all sub-bands, then coding complexity is reduced, but signal quality deteriorates because energy distribution is not considered
Solution Approach 1:
The patent applies sinusoidal coding selectively to specific sub-bands based on their energy characteristics rather than uniformly to all sub-bands. The encoder calculates energy for each sub-band and identifies those with energy exceeding a threshold, then applies sinusoidal coding only to these high-energy sub-bands. This local differentiation optimizes signal quality where it matters most while reducing unnecessary coding complexity in low-energy regions.
2Device complexity
If sinusoidal coding is applied to all sub-bands, then signal representation is simplified, but bit efficiency deteriorates due to insufficient bit allocation
Solution Approach 1:
The patent dynamically changes the parameter of sinusoidal coding application based on sub-band energy characteristics. By calculating energy for each sub-band and comparing it against a threshold, the system adapts its coding strategy: applying sinusoidal coding to high-energy sub-bands where it provides maximum benefit, and using alternative coding methods for low-energy sub-bands. This parameter-based adaptation maximizes bit efficiency under constrained bit allocation.
3Manufacturing precision
If bit allocation is increased for sinusoidal coding, then signal quality improves, but transmission bandwidth requirements increase
Solution Approach 1:
The patent concentrates bit allocation resources on sub-bands with high energy content that contribute most to perceived signal quality. By identifying and prioritizing these critical sub-bands for sinusoidal coding, the system achieves maximum quality improvement with minimum bitrate investment. Low-energy sub-bands receive alternative coding treatment, avoiding wasteful bit consumption and optimizing the overall bitrate-quality tradeoff.
Data Source
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.