Transform Audio Codec Sign Encoding Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing transform domain coding schemes face inefficiencies in bit allocation, particularly at low or moderate bit-rates, leading to unsatisfactory encoding results due to the unnecessary encoding of residual vectors that do not significantly impact the audio signal's quality.
Innovation Solution
A method that determines the position and structure of residual vectors in the frequency domain, encoding only the amplitude of coefficients and selectively encoding the sign when a change would be audible, thereby optimizing bit distribution and preserving quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the sign of all residual vector coefficients is encoded, then the audio signal quality is improved, but the number of bits required increases
Solution Approach 1:
The patent applies local quality by differentiating the encoding treatment of different residual vector coefficients based on their individual characteristics. Specifically, it encodes the sign of coefficients that meet certain criteria (e.g., those with significant impact on perceived quality) while omitting encoding for others. This selective approach optimizes bit allocation by focusing resources on coefficients that locally matter most to audio quality rather than uniformly encoding all coefficients.
Solution Approach 2:
The patent implements partial action by encoding only a subset of residual vector coefficient signs rather than all of them. It uses criteria such as spectral flatness measures, energy thresholds, or positional information to determine which coefficients require sign encoding. This partial encoding approach achieves satisfactory audio quality at lower bit rates by performing the useful action (sign encoding) only where necessary rather than excessively applying it to all coefficients.
2Productivity
If fewer bits are allocated to residual vector encoding, then the bit rate is reduced, but the audio signal quality deteriorates
Solution Approach 1:
The patent changes parameters by introducing dynamic criteria for sign encoding based on local signal characteristics such as spectral flatness, energy distribution, and frequency position. These parameter-based criteria allow the encoder to adaptively determine which coefficients need sign encoding, optimizing the balance between bit rate and quality. By changing from a fixed encoding approach to a parameter-driven selective approach, the system achieves better bit rate efficiency without significant quality loss.
Solution Approach 2:
The patent applies local quality by making encoding decisions based on local characteristics of each residual vector coefficient rather than applying a global encoding strategy. It evaluates local properties such as the spectral context, energy level, and position of each coefficient to determine whether sign encoding is necessary. This localized approach ensures that bits are allocated efficiently to regions of the spectrum where they will have the most impact on perceived quality.
3Quantity of substance
If the sign of residual vector coefficients is not encoded, then the number of bits is reduced, but the reconstructed audio signal accuracy decreases
Solution Approach 1:
The patent applies local quality by selectively encoding signs only for coefficients where it locally matters for reconstruction accuracy. It uses criteria such as spectral flatness measures, energy thresholds, and frequency position to identify coefficients whose sign information is critical. For coefficients where the local characteristics indicate low sensitivity to sign changes (e.g., in noisy or high-frequency regions), the sign is omitted, reducing bit requirements without significantly impacting overall reconstruction accuracy.
Solution Approach 2:
The patent introduces intermediary criteria and decision mechanisms that mediate between the need for compression and reconstruction accuracy. It uses intermediate calculations such as spectral flatness measures, energy comparisons, and positional analysis to determine which coefficients require sign encoding. These intermediary evaluations act as a bridge, allowing the system to make informed decisions about where sign encoding is necessary to maintain accuracy while minimizing overall bit requirements.
Data Source
AI summary
Methods and devices for efficient encoding/decoding of a time segment of an audio signal. The methods comprise deriving an indicator, z, of the position in a frequency scale of a residual vector associated with the time segment of the audio signal, and deriving a measure, Φ, related to the amount of structure of the residual vector. The methods further comprise determining whether a predefined criterion involving the measure Φ, the indicator z and a predefined threshold Θ, is fulfilled, which corresponds to estimating whether a change of sign of at least some of the non-zero coefficients of the residual vector would be audible after reconstruction of the audio signal time segment. The respective amplitude of the coefficients of the residual vector is encoded, and the signs of the coefficients of the residual vector are encoded only when it is determined that the criterion is fulfilled, and thus that a change of sign would be audible.