Audio Data Interpolation at Edit Boundaries
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Solution Overview
Problem
Existing audio editing methods often result in discontinuities at edit boundaries, leading to poor audio quality due to noise and unwanted audio data, which are difficult to correct manually.
Innovation Solution
The method involves automatically correcting audio data by interpolating values across edit boundaries, using identified amplitude and phase values from surrounding samples to smooth transitions, thereby reducing discontinuities and improving audio quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual correction methods are used to fix audio discontinuities at edit boundaries, then audio quality can be improved, but the editing process becomes complex and time-consuming
Solution Approach 1:
The system automatically detects edit boundaries and performs interpolation correction without requiring user intervention. The audio editing system self-corrects discontinuities by analyzing surrounding audio samples and generating corrected audio data, eliminating the need for manual correction operations.
Solution Approach 2:
The system performs correction actions automatically at the time of editing by interpolating audio data surrounding edit boundaries. This preliminary automatic correction prevents discontinuities from affecting final audio quality, eliminating the need for subsequent manual correction steps.
2Reliability
If cross-fading is used to smooth transitions across edit boundaries, then audio continuity improves, but more audio data is required on each side of the boundary
Solution Approach 1:
The interpolation method applies different weighting factors to surrounding audio samples based on their proximity to the edit boundary. Samples closer to the boundary receive higher weighting factors, while distant samples receive lower weights, creating a localized correction effect that requires minimal audio data on each side of the boundary.
Solution Approach 2:
The system changes the parameter of audio data by interpolating amplitude and phase values at edit boundaries. By modifying these parameters through mathematical interpolation rather than requiring extensive audio data, the system achieves smooth transitions with minimal surrounding samples.
3Reliability
If interpolation is used to correct audio data at edit boundaries, then audio quality improves with minimal data requirement, but the processing complexity increases
Solution Approach 1:
The correction process is segmented into distinct steps: detecting edit boundaries, identifying surrounding audio samples, extracting amplitude and phase information, performing interpolation calculations, and generating corrected audio data. This segmentation allows each step to be optimized independently and reduces overall processing complexity.
Solution Approach 2:
The system uses intermediate representations of audio data (amplitude spectra and phase spectra) as mediators between the original audio samples and the final corrected audio. This intermediary approach simplifies the interpolation process by working with frequency-domain representations rather than directly manipulating time-domain waveforms.
Data Source
AI summary
Systems, methods, and computer program products are provided for editing digital audio data. In some implementations a method is provided that includes receiving digital audio data, identifying a modification to a portion of the digital audio data, and automatically correcting audio data surrounding one or more edit boundaries resulting from the identified modification including interpolating audio data from a region associated with the one or more edit boundaries.