Voice Input Anomaly Detection via Audio Signal Analysis
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Solution Overview
Problem
There is no effective method to determine when the sound reception hole of an electronic device is blocked, leading to impaired audio signal collection, which affects user experience as users are not notified of the issue or provided with a remedy.
Innovation Solution
A voice input exception determining method that assesses the amplitude and energy distribution of audio signals by performing Fourier frequency domain conversion, calculating high and low-frequency energy values, and adjusting the audio collection module to enable alternative sound reception when abnormalities are detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sound reception hole is disposed on the housing to collect audio signals, then audio collection capability is improved, but the sound reception hole is easily blocked by the complex environment, causing sound information collection to be affected
Solution Approach 1:
The patent implements a feedback mechanism by continuously monitoring the audio signal characteristics (amplitude, energy distribution, frequency spectrum) from the audio collection module and comparing them against expected ranges. When deviations indicating blockage are detected, the system provides feedback to trigger notifications to users or switch to alternative audio collection modes, thereby resolving the reliability issue while maintaining the sound reception hole design
Solution Approach 2:
The patent changes the parameter monitoring approach by analyzing multiple audio signal parameters including amplitude values, energy distribution across frequency bands, and spectral characteristics. By monitoring changes in these parameters over time, the system can detect blockage conditions and adapt its behavior, thus maintaining reliable audio collection despite environmental challenges
2Device complexity
If only algorithm normality of collected audio signal is detected, then detection simplicity is maintained, but no effective method exists for detecting sound reception exceptions caused by blocked sound reception holes
Solution Approach 1:
The patent segments the audio signal analysis into multiple independent components: amplitude value detection, energy distribution analysis across different frequency bands, and spectral characteristic examination. Each segment is processed separately and then integrated to form a comprehensive blockage detection judgment, thereby enhancing detection precision while maintaining manageable system complexity
Solution Approach 2:
The patent applies partial action by selectively analyzing specific frequency bands and audio signal characteristics that are most indicative of blockage conditions. Rather than processing the entire audio spectrum equally, the system focuses computational resources on critical parameters such as low-frequency energy distribution and amplitude thresholds, achieving effective blockage detection with optimized complexity
3Device complexity
If no notification or remedy is provided for sound reception exceptions, then system simplicity is maintained, but user experience is adversely affected
Solution Approach 1:
The patent implements self-service by automatically detecting sound reception exceptions and providing remedies without requiring user intervention for diagnosis. The system autonomously monitors audio signal quality, identifies blockage conditions, and executes corrective actions such as notifying users through the interface or switching to alternative audio collection modes, thereby improving user experience while adding minimal complexity to the system structure
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method effectively detects and addresses sound reception exceptions by comprehensively analyzing time and frequency domain features of audio signals, improving microphone input exception detection precision and user experience by notifying users and enabling alternative audio collection.
Implementation Method 1
performing Fourier frequency domain conversion on the audio signal, to determine an energy value of the audio signal
Data Source
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AI summary
A voice input exception determining method, an apparatus, a terminal, and a storage medium are provided. The method is applied to an electronic device including an audio collection module, and includes: determining whether an amplitude value of an audio signal collected by the audio collection module is less than a preset amplitude threshold and/or whether energy distribution of the audio signal meets a preset condition; and if the amplitude value of the audio signal is less than the preset amplitude threshold and/or the energy distribution of the audio signal does not meet the preset condition, determining that voice input of the electronic device is abnormal. A solution provided in the present invention resolves a prior-art problem that there is no effective method for determining a sound reception exception caused when a sound reception hole of the electronic device is blocked.