Audio Signal Classification Using Guidance Features for Fine Detection
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Solution Overview
Problem
Existing audio detection technologies struggle with low accuracy and high implementation complexity in distinguishing voice signals from non-voice signals, particularly in scenarios requiring fine classification, leading to inadequate detection results.
Innovation Solution
An audio signal processing method involving signal spreading and enhancement techniques, combined with neural networks and classification models, to enhance and filter audio signals, improving detection accuracy by subdividing signal types into subtypes for precise classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional audio detection methods are used to distinguish voice signals from non-voice signals, then the implementation is simpler, but the detection accuracy is low
Solution Approach 1:
The patent divides the audio signal classification task into multiple stages: first classifying audio signals into broad categories (voice/non-voice), then further subdividing into specific types (speaking, singing, laughing, etc.). This hierarchical segmentation approach improves detection accuracy by allowing specialized processing for each category while keeping the overall system manageable in complexity.
Solution Approach 2:
The patent introduces intermediate classification layers between the initial voice/non-voice detection and the final specific signal type identification. These intermediate categories act as mediators that guide the classification process, improving accuracy by breaking down the complex classification task into manageable steps with clear decision boundaries.
2Measurement precision
If fine classification of signal types is performed to improve detection accuracy, then the detection precision is improved, but the computational complexity increases
Solution Approach 1:
The patent segments the classification process into multiple hierarchical levels, where each level handles a specific aspect of signal classification. This allows the system to achieve fine classification precision without requiring all computational resources to be dedicated to a single complex classification task, thereby managing computational complexity more effectively.
Solution Approach 2:
The patent applies classification processing at different levels of detail appropriate to each signal category. Not all audio signals require the same level of fine classification - the system applies partial classification where sufficient and more detailed classification where needed, optimizing the balance between precision and computational complexity.
Data Source
AI summary
The present disclosure provides methods, devices, and computer-readable mediums for audio signal processing. In some embodiments, a method executed by an electronic device includes obtaining guidance features corresponding to an audio signal to be processed, the guidance features indicating distinguishable features of at least one signal type of at least one signal category. The method further includes extracting, according to the guidance features, target audio features corresponding to the audio signal. The method further includes determining, according to the target audio features, a target signal type of the audio signal from among the at least one signal type of the at least one signal category. The method further includes performing corresponding processing according to the target signal type of the audio signal.