Audio Signal Processing Using Learned Difference Signals
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Solution Overview
Problem
Existing techniques lack a mathematical basis for achieving bit extension in music signals, resulting in suboptimal sound quality due to reliance on human adjustment of gain values.
Innovation Solution
A signal processing apparatus and method that utilizes machine learning to generate a difference signal based on a re-quantized audio signal and an original sound signal, using a prediction coefficient learned from training data, to combine with the input signal and enhance sound quality to a higher bit length.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If human adjustment of gain values is used to achieve bit extension, then sound quality can be improved, but the process requires manual parameter adjustments and results in variability
Solution Approach 1:
The system uses machine learning models that automatically learn optimal gain values and difference signal characteristics from training data, eliminating the need for manual parameter adjustment. The model self-optimizes by processing training signals and generating appropriate output parameters without human intervention.
Solution Approach 2:
The patent replaces manual mechanical adjustment of gain values with an automated machine learning-based calculation system. The difference signal generation unit computes optimal parameters mathematically based on learned patterns from training data, substituting human operator actions with algorithmic processing.
2Manufacturing precision
If human adjustment of gain values is used to achieve bit extension, then sound quality can be improved, but consistency and reliability are reduced due to variability
Solution Approach 1:
The machine learning model consistently applies learned patterns to generate difference signals and gain values, ensuring uniform processing across different input signals. The model's trained parameters provide reliable and repeatable results without human variability.
Solution Approach 2:
The system dynamically adjusts gain values and difference signal parameters based on the specific characteristics of the input signal, using mathematically determined values from the machine learning model. This ensures optimal sound quality for each signal while maintaining consistency through algorithmic rather than manual parameter selection.
3Extent of automation
If mathematical-based bit extension is achieved through machine learning, then consistency and automation are improved, but the system complexity increases
Solution Approach 1:
The machine learning model is trained in advance on a large dataset of audio signals to learn the characteristics of difference signals and optimal gain values. This preliminary training phase stores learned patterns in the model parameters, allowing rapid automated processing during actual use without complex real-time calculations.
Solution Approach 2:
The patent introduces a machine learning model as an intermediary component between the input audio signal and the difference signal generation. This model acts as a mathematical bridge that translates input signals into optimized output parameters based on learned patterns, simplifying the overall system architecture while enabling sophisticated processing.
Data Source
AI summary
The present technology relates to a signal processing apparatus, a signal processing method, and a program that are to enable acquisition of a signal with higher sound quality.A signal processing apparatus includes: a difference-signal generation unit configured to generate, on the basis of an input signal and a prediction coefficient that is acquired by learning with, as training data, a difference signal based on a re-quantized signal for learning acquired by re-quantization of an original sound signal and the original sound signal, the difference signal corresponding to the input signal; and a combining unit configured to combine the difference signal generated and the input signal. The present technology is applicable to a signal processing apparatus.