Noise Suppression Device Using Representative Power Spectrum
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Solution Overview
Problem
Conventional noise suppression devices require complex calculations and process large amounts of information, leading to underestimation of voice components and degradation in voice quality due to averaging of spectral components.
Innovation Solution
A noise suppression device that selects the power spectrum with the larger value in each group as the representative spectrum for noise suppression calculations, reducing information processing and preventing voice component underestimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional noise suppression devices average multiple power spectrum components to reduce information processing, then the amount of information to be processed is reduced, but voice components are underestimated and voice quality degrades
Solution Approach 1:
The patent creates a representative power spectrum that copies the characteristics of the strongest spectral component in each frequency band. Instead of averaging all components, it selects and replicates the most significant voice component, preserving voice quality while reducing the information processing burden by working with a single representative spectrum per band.
2Measurement precision
If conventional noise suppression devices perform complex calculations for each power spectrum component, then noise suppression accuracy is improved, but the amount of information to be processed increases
Solution Approach 1:
The patent segments the frequency spectrum into multiple bands and processes each band independently by selecting only the strongest power spectrum component. This segmentation approach maintains noise suppression accuracy within each band while dramatically reducing the total information volume by eliminating redundant processing of weaker components across the entire spectrum.
3Device complexity
If conventional noise suppression devices average spectral components to simplify processing, then device complexity is reduced, but voice components are suppressed and voice quality degrades
Solution Approach 1:
The patent applies local quality by treating different frequency bands differently - selecting the strongest component in each band based on its local characteristics rather than applying a uniform averaging operation across all frequencies. This preserves the unique properties of voice components in each band, maintaining voice quality while simplifying the overall device complexity.
Data Source
Figure 1
Figure 2
Figure 3(a)~3(c)
AI summary
A band separating unit 5 carries out a band division of a plurality of power spectra into which an input signal is converted by a time-to-frequency converting unit 2 to combine power spectra into each subband, and a band representative component generating unit 6 defines a power spectrum having a maximum among the plurality of power spectra within each subband as a representative power spectrum. A noise suppression amount generating unit 7 calculates an amount of noise suppression for each subband by using the representative power spectrum and a noise spectrum, and a noise suppressing unit 9 suppresses the amplitudes of the power spectra according to the amount of noise suppression.