Audio Signal Processing with Label Concatenation for Generative Synthesis
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Solution Overview
Problem
Current audio signal processing methods using machine learning models face challenges in effectively generating high-quality audio signals that match user inputs, particularly in incorporating features like quality reference information and recording environment details, and in efficiently synthesizing audio signals with higher resolution.
Innovation Solution
An audio signal processing device that acquires labels indicating input modal features, concatenates these labels with the input modal, and uses a generative model to generate audio signals, employing skip connections and FiLM for improved synthesis, and trains models to generate audio frequency characteristics with higher resolution, allowing for the generation of high-quality audio signals that match user inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional audio signal processing methods are used, then the process is simpler, but the audio quality and resolution are insufficient
Solution Approach 1:
The audio signal processing is divided into multiple stages: feature extraction from input modal, label acquisition for group features, concatenation of features and labels, and audio signal generation. This segmentation allows each component to be optimized independently while maintaining overall system manageability.
Solution Approach 2:
The system performs preliminary feature extraction and label acquisition before audio signal generation. By preparing quality reference information, recording environment information, and background sound information in advance, the system ensures high-quality audio output without adding complexity during the actual generation process.
2Measurement precision
If feature information is incorporated to improve audio quality, then the audio signal accuracy improves, but the processing complexity increases
Solution Approach 1:
The label acquisition module serves multiple functions: it identifies group features, determines quality reference information, captures recording environment characteristics, and identifies background sound properties. This multi-functionality reduces the need for separate processing modules while maintaining comprehensive feature information.
Solution Approach 2:
The concatenation operation acts as an intermediary that integrates feature information from the input modal with group feature labels. This intermediary step efficiently combines multiple information sources without requiring complex integration logic, maintaining processing simplicity while improving input matching accuracy.
Data Source
AI summary
An audio signal processing device for generating an audio signal for an input modal is disclosed. The audio signal processing device includes a processor. The processor is configured to: acquire a label indicating the feature of a group to which the input modal belongs; concatenate the acquired label to the input modal; and input the input modal and the acquired label into a generative model to generate an audio signal.