Spectral Peak Position Coding for Periodic and Sparse Audio Signals
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Solution Overview
Problem
Conventional audio coding methods are inefficient in encoding spectral peak positions due to abrupt changes in distribution, as they often rely on a single coding scheme that fails to adapt to varying peak distributions, leading to increased bit consumption.
Innovation Solution
A method that dynamically selects between two lossless spectral peak position coding schemes based on the maximum distance between peaks, using delta coding for periodic distributions and sparse coding for sparse distributions, optimizing bit usage by choosing the scheme that requires the least number of bits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single lossless coding scheme is used for spectral peak positions, then the coding structure is simple, but the bit consumption increases due to inability to adapt to varying peak distributions
Solution Approach 1:
The patent implements dynamic selection between two different lossless coding schemes based on the actual spectral peak distribution characteristics. The encoder determines which coding scheme (first or second) is more suitable by analyzing the spectral peaks, and this selection adapts to different signal conditions, thereby reducing bit consumption while maintaining manageable complexity through automated decision-making.
2Productivity
If delta coding is used for periodic spectral peaks, then the coding efficiency is high for periodic distributions, but the performance degrades for sparse distributions
Solution Approach 1:
The patent changes the coding parameter (coding scheme selection) based on the spectral peak distribution characteristics. By analyzing whether the spectral peaks exhibit periodic or sparse distribution patterns, the system selects the appropriate coding scheme, thereby maintaining high coding efficiency across different signal types rather than being constrained to a single approach.
Solution Approach 2:
The system dynamically adapts the coding approach by selecting between two different lossless coding schemes based on the actual spectral peak distribution. This dynamic selection mechanism allows the system to optimize coding efficiency for each specific signal condition, whether periodic or sparse, rather than using a static single-scheme approach.
3Productivity
If sparse coding is used for sparse spectral peaks, then the coding efficiency is high for sparse distributions, but the performance degrades for periodic distributions
Solution Approach 1:
The patent implements parameter change by selecting different coding schemes based on spectral peak distribution analysis. When sparse distribution is detected, the system applies the second coding scheme optimized for sparse peaks, while switching to the first coding scheme for periodic distributions, thereby maintaining high efficiency across varying signal conditions.
Solution Approach 2:
The system dynamically adjusts the coding strategy by selecting between two specialized coding schemes based on the actual spectral peak distribution characteristics. This dynamic adaptation ensures optimal coding efficiency whether the signal exhibits sparse or periodic peak patterns, rather than being limited to a fixed approach.
Data Source
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AI summary
A method and an audio coder for coding spectral peak positions of an audio signal segment are provided. The method comprises determining which one out of two lossless coding schemes requires the least number of bits to code the spectral peak positions of an audio signal segment; and selecting the coding scheme that requires the least number of bits to code the spectral peak positions of the audio signal segment. A first one of the two lossless coding schemes is suitable for periodic or semi-periodic spectral peak position distributions; and a second one of two lossless coding schemes is suitable for sparse spectral peak position distributions.