Signal Processing Device for Compressed Audio Quality Restoration
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Solution Overview
Problem
Existing methods for improving sound quality of compressed sound source signals struggle to accurately restore the original sound quality, requiring manual gain adjustments and relying heavily on human audition, which is inefficient and unreliable.
Innovation Solution
A signal processing device and method that calculates a prediction coefficient using machine learning to generate a difference signal based on the compressed sound source signal, allowing for the synthesis of a high-quality sound signal by adding the difference signal to the compressed sound source signal, effectively improving sound quality without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual gain adjustment is performed to improve sound quality, then sound quality can be optimized to some extent, but the process is time-consuming and unreliable
Solution Approach 1:
The system performs automatic gain adjustment without human intervention. The calculation unit automatically computes gain values based on the compressed sound source signal and prediction coefficients, eliminating the need for manual auditory optimization while achieving consistent sound quality improvement
Solution Approach 2:
The patent replaces manual auditory adjustment with an automated computational system. The calculation unit uses mathematical operations and prediction coefficients to determine gain values, substituting the mechanical process of human listening and adjustment with an automated digital system
2Manufacturing precision
If manual gain adjustment is performed, then sound quality can be optimized, but the process requires human audition which is inefficient
Solution Approach 1:
The system autonomously performs gain adjustment using computational algorithms. The calculation unit automatically determines optimal gain values based on the compressed sound source signal characteristics, eliminating the need for human auditors and significantly improving optimization efficiency
Solution Approach 2:
The patent replaces the mechanical process of human auditory evaluation with automated computational algorithms. The calculation unit uses mathematical predictions and signal processing to optimize sound quality, transforming a manual, time-consuming process into an efficient automated system
3Manufacturing precision
If the compressed sound source signal is processed to restore original quality, then sound quality improves, but the complexity of the processing system increases
Solution Approach 1:
The patent divides the sound quality improvement process into distinct functional modules: a calculation unit for computing gain values, a difference signal generation unit for creating the difference signal, and a synthesis unit for combining signals. This segmentation reduces overall system complexity by making each component's function clear and manageable
Solution Approach 2:
The patent introduces prediction coefficients as an intermediary element that simplifies the processing. These pre-computed coefficients capture the relationship between compressed and original signals, allowing the system to generate accurate difference signals through simple multiplication operations rather than complex analysis
4Manufacturing precision
If manual gain adjustment is performed, then sound quality can be optimized, but the final gain value determination is subjective and unreliable
Solution Approach 1:
The patent replaces subjective human judgment with objective computational algorithms. The calculation unit determines gain values through mathematical operations on the compressed sound source signal, producing consistent and reliable results that do not vary with human auditors or listening conditions
Solution Approach 2:
The system uses prediction coefficients that are derived from analyzing the relationship between compressed and original signals. This feedback mechanism allows the system to automatically adjust gain values based on the actual signal characteristics, ensuring reliable and consistent sound quality improvement without human subjectivity
Data Source
AI summary
The present technology relates to a signal processing device, a method, and a program that can obtain a signal with higher sound quality.The signal processing device includes: a calculation unit that calculates a parameter for generating a difference signal corresponding to an input compressed sound source signal on the basis of a prediction coefficient and the input compressed sound source signal, the prediction coefficient being obtained by learning using, as training data, a difference signal between an original sound signal and a learning compressed sound source signal obtained by compressing and coding the original sound signal; a difference signal generation unit that generates the difference signal on the basis of the parameter and the input compressed sound source signal; and a synthesis unit that synthesizes the generated difference signal and the input compressed sound source signal. The present technology can be applied to a signal processing device.