Multi-Band Resonator Audio Processing for Selective Noise Removal
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current sound signal processing methods, such as spectral subtraction, beam forming, and source separation, are inefficient in effectively removing noise across all audible bands, leading to suboptimal signal clarity.
Innovation Solution
A sound signal processing apparatus comprising a band separator with multiple resonators and signal processing blocks that separate and process sound signals based on frequency bands, using amplifiers and sign determiners to differentiate and amplify signals above a threshold intensity, thereby enhancing noise removal and signal clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If spectral subtraction, beam forming, or source separation algorithms are used to remove noise, then noise removal capability is improved, but processing complexity and computational requirements increase
Solution Approach 1:
The audio signal is divided into multiple frequency bands using bandpass filters, allowing noise removal to be applied selectively to specific bands rather than processing the entire spectrum uniformly. This segmentation reduces computational complexity while maintaining effective noise removal where needed.
Solution Approach 2:
Different processing strategies are applied to different frequency bands based on their specific characteristics. Bands with high noise content receive aggressive noise removal, while clean bands are preserved with minimal processing, optimizing both noise removal effectiveness and computational efficiency.
2Ease of manufacture
If uniform processing is applied to all audible bands, then simplicity of implementation is maintained, but noise removal efficiency across all bands deteriorates
Solution Approach 1:
The audible spectrum is segmented into multiple frequency bands using bandpass filters with center frequencies distributed across the spectrum. This allows the system to move from uniform processing to targeted processing of specific frequency regions, improving noise removal efficiency while maintaining manageable complexity.
Solution Approach 2:
The system varies processing parameters (such as gain adjustments and noise removal intensity) across different frequency bands based on their individual characteristics, rather than applying uniform parameters to all bands. This enables optimized noise removal for each band's specific noise profile.
3Object-affected harmful factors
If multiple microphones are used for beam forming and source separation, then noise removal capability is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces the need for multiple physical microphones with a single microphone combined with digital signal processing. By using bandpass filters and frequency-domain processing, the system achieves noise removal capabilities similar to multi-microphone systems without requiring additional hardware sensors.
Solution Approach 2:
Digital signal processing algorithms act as intermediaries that simulate the spatial filtering effects of multiple microphones. The processing blocks analyze and manipulate frequency components to achieve noise removal and source separation that would traditionally require multiple physical sensors.
4Adaptability or versatility
If a wide band vibrator is used in a microphone, then coverage of all audible bands is achieved, but selectivity for specific frequency bands deteriorates
Solution Approach 1:
The wide band signal captured by the microphone is segmented into multiple frequency bands using bandpass filters. This allows the system to maintain broad frequency coverage while achieving high selectivity for specific bands through digital filtering, enabling targeted processing of individual frequency regions.
Solution Approach 2:
The bandpass filters are applied preliminarily to separate frequency bands before subsequent noise removal and processing steps. This preliminary segmentation enables more effective and selective processing of each frequency band, improving overall frequency selectivity throughout the signal chain.
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
The apparatus significantly improves noise removal efficiency, increasing the signal-to-noise ratio and enhancing signal clarity by selectively processing sound signals based on frequency bands and intensity thresholds, resulting in improved audio quality.
Implementation Method 1
The band separator may include a plurality of resonators configured to separate the sound signals based on the frequency bands
Data Source
AI summary
Sound signal processing apparatuses and methods of operating the same are provided. The sound signal processing apparatus includes: a band separator configured to separate sound signals into frequency bands; an adder configured to add sound signals; and a signal processor that is arranged between the band separator and the adder and comprises a plurality of signal processing blocks. The band separator includes elements for separating the sound signals into frequency bands, and the elements correspond one to one to the signal processing blocks.