Audio Coding Preprocessing Selective Long Term Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current speech and audio coding technologies perform unnecessary Long Term Prediction (LTP) operations on all input frame signals, including silence and unvoiced signals, which reduces coding efficiency and increases complexity.
Innovation Solution
A preprocessing method that identifies whether a current frame signal requires Long Term Correlation (LTC) removal based on characteristic information, and if not, performs only Short Term Correlation (STC) removal, or both LTC and STC removal if necessary, thereby optimizing coding operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If LTP operation is performed for all input frame signals, then long-term redundancy elimination is achieved, but coding complexity and resource consumption increase
Solution Approach 1:
The patent applies partial action by performing LTP operation selectively rather than on all frames. It identifies that LTP is primarily beneficial for voiced signals and applies it only to those frames that meet specific criteria (voiced frame detection), while skipping silence and unvoiced frames. This partial application reduces coding complexity and resource consumption while maintaining effective long-term redundancy elimination where needed.
Solution Approach 2:
The patent changes the parameter of LTP operation applicability from universal (all frames) to conditional (voiced frames only). By introducing voiced frame detection based on signal characteristics, it dynamically adjusts whether LTP operation is performed on each frame, optimizing the balance between compression efficiency and coding complexity.
2Reliability
If LTP operation is performed on all frames including silence and unvoiced signals, then long-term prediction is applied uniformly, but resource consumption increases without significant benefit
Solution Approach 1:
The patent changes the applicability parameter of LTP operation from universal to selective based on frame type detection. By detecting whether a frame is voiced, silence, or unvoiced, it adjusts the LTP operation parameter (perform or skip) dynamically, ensuring reliable coding only where beneficial while conserving resources.
Solution Approach 2:
The coding system performs self-service by automatically detecting frame characteristics and making decisions about LTP operation application. The voiced frame detection mechanism enables the system to identify which frames benefit from LTP and apply it autonomously without external control, optimizing resource usage while maintaining coding reliability.
Data Source
AI summary
The present disclosure relates to coding and decoding technologies, and discloses a preprocessing method, a preprocessing apparatus, and a coding device. The preprocessing method includes: obtaining characteristic information of a current frame signal; identifying whether the current frame signal requires no coding operation of removing LTC according to the characteristic information of the current frame signal and preset information; and if identifying that the current frame signal requires no coding operation of removing LTC, performing the coding operation of removing STC for the current frame signal; and if identifying that the current frame signal requires the coding operation of removing LTC, performing the coding operations of removing both LTC and STC for the current frame signal. Through the technical solution provided herein, the coding operation of removing LTC is performed for only part of the input frame signals.