Adaptive Time Scaling Method for Audio DSP Efficiency
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Solution Overview
Problem
Existing time scaling methods in AV players, such as Phase Vocoder, Minimum Perceived Loss Time Expansion/Compression, and Time Domain Harmonic Scaling, require tedious calculations to determine the maximum index for autocorrelogram establishment, which is inefficient and unnecessary for DSP chips.
Innovation Solution
A multiple level adaptive method that calculates a cross-correlation function's magnitude and compares it with threshold values to efficiently determine the maximum index, reducing the need for DSP chips to calculate all autocorrelogram magnitudes by selectively calculating reference magnitudes based on threshold comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional autocorrelogram establishment methods are used to determine the maximum index, then the time scaling accuracy is maintained, but the computational complexity and processing time increase significantly
Solution Approach 1:
The patent segments the autocorrelogram establishment process into multiple stages: initial rough estimation using simplified calculations, followed by refined adjustments only in critical regions. This segmentation allows the system to maintain accuracy where needed while reducing unnecessary computations in other areas, directly resolving the contradiction between measurement precision and device complexity.
Solution Approach 2:
The patent applies partial action by calculating autocorrelogram magnitudes selectively rather than computing all magnitudes exhaustively. The system performs calculations only for indices that are likely to contain the maximum magnitude based on preliminary analysis, thereby maintaining time scaling accuracy while significantly reducing the computational burden on the DSP chip.
2Manufacturing precision
If all autocorrelogram magnitudes are calculated to ensure accurate maximum index determination, then the time scaling quality is preserved, but the processing time increases
Solution Approach 1:
The patent implements preliminary action by performing initial estimates and preliminary calculations to identify the most promising regions for maximum magnitude before conducting full autocorrelogram analysis. This preliminary step allows the system to focus subsequent computational resources on critical areas, ensuring time scaling quality while minimizing overall processing time through strategic prioritization.
Solution Approach 2:
The patent applies skipping by allowing the system to bypass unnecessary calculation steps when preliminary analysis indicates certain regions cannot contain the maximum magnitude. The method rushes through non-critical calculations while maintaining thorough analysis in promising regions, thereby preserving time scaling quality without the penalty of computing all magnitudes exhaustively.
3Measurement precision
If the DSP chip performs comprehensive autocorrelogram calculations, then the maximum index accuracy is ensured, but the computational efficiency decreases
Solution Approach 1:
The patent applies local quality by concentrating computational effort on specific local regions of the autocorrelogram where the maximum magnitude is most likely to occur, rather than uniformly processing the entire autocorrelogram. This localized approach ensures maximum index accuracy in critical regions while improving overall computational efficiency by avoiding redundant calculations in non-promising areas.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting calculation precision and computational depth based on local characteristics of the autocorrelogram. The system changes computational parameters adaptively - using higher precision where needed and lower precision where sufficient - thereby maintaining maximum index accuracy while significantly improving computational efficiency through context-aware resource allocation.
Data Source
AI summary
A multiple step adaptive method for time scaling. Synthesizing S3[n] signal from signal S1[n]signal and S2[n]signal. Comprising following steps: (a) calculating a first magnitude of a cross-correlation function of S1[n]signal and S2[n]signal according to a first index; (b) comparing the first magnitude with a threshold value; (c) if first magnitude is smaller than threshold value, calculating a first reference magnitude of cross-correlation function of S1[n]signal and S2[n]signal according to a first reference index behind the first index by a first determined number, or calculating a second reference magnitude of the cross-correlation function of the S1[n] signal and the S2[n] signal according to a second reference index behind the first index by a second number; (d) synthesizing the S3[n] signal by adding S1[n]signal to the S2[n] signal in accordance with a maximum index corresponding to a largest magnitude among all the magnitudes calculated in (c).