Buffered Audio Filtering Using Power Thresholds for Noise Reduction
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Solution Overview
Problem
Existing audio recording technologies fail to effectively reduce ambient noises, resulting in suboptimal audio quality.
Innovation Solution
A method and apparatus that convert analogue audio data into digital data, cache it in a buffer, and filter it using preset peak power and average power gradient thresholds to enhance audio quality by removing noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If existing audio recording technologies are used, then recording simplicity is maintained, but ambient noise reduction capability is insufficient
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing power threshold values before audio processing. The system computes peak power thresholds and average power gradient thresholds in advance, then uses these pre-computed thresholds during actual audio filtering to reduce ambient noise. This approach prepares the filtering criteria beforehand, enabling efficient noise reduction without adding complex real-time computation during audio processing.
Solution Approach 2:
The patent employs parameter changes by dynamically adjusting filtering parameters (peak power threshold and average power gradient threshold) based on the characteristics of the recorded audio signal. The system analyzes the audio data to determine appropriate threshold values, then applies these parameterized thresholds to filter out ambient noise while preserving speech. This allows the filtering mechanism to adapt to different recording conditions without requiring complex manual configuration.
2Manufacturing precision
If no filtering is applied, then processing speed is maintained, but audio quality deteriorates due to ambient noise
Solution Approach 1:
The patent replaces complex mechanical or hardware-based noise reduction systems with a software-based digital filtering approach. Instead of using physical acoustic filters or complex hardware processing, the system uses digital signal processing algorithms that analyze audio data and apply mathematical filtering based on power thresholds. This substitution achieves high audio quality with lower processing overhead compared to traditional hardware-based noise reduction systems.
Solution Approach 2:
The patent introduces an intermediary filtering mechanism that processes audio data between recording and playback. The system inserts a digital filtering stage that uses pre-computed power thresholds to selectively remove ambient noise components while preserving speech signals. This intermediary processing layer acts as a mediator that enhances audio quality without requiring complete reprocessing of the entire audio stream, thus maintaining processing efficiency.
3Object-affected harmful factors
If complex filtering algorithms are used, then noise reduction effectiveness improves, but computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the noise reduction process into distinct stages: first computing peak power thresholds, then calculating average power gradients, and finally applying filtering based on these separate threshold values. This segmented approach breaks down the complex filtering task into manageable components, each with its own threshold criterion. The segmentation enables effective noise reduction while keeping each processing stage computationally simple and easy to implement.
Data Source
AI summary
A method and apparatus for processing a recording is described. Analogue audio data is recorded and converted into digital audio data. The digital audio data is cached to a preset buffer. The digital audio data is called back from the buffer and is filtered according to a preset peak power threshold and an average power gradient threshold to obtain filtered audio data.