Audio Signal Noise Reduction Using Dual Envelope Thresholds
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Solution Overview
Problem
Existing audio signal processing technologies fail to effectively distinguish and reduce noise from intended audio signals, leading to degraded communication quality, particularly in telecommunications for hearing-impaired users.
Innovation Solution
A computer-implemented method that separates audio signals into multiple frequency bands, calculates envelopes to determine the presence of intended audio signals, and attenuates noise-laden bands based on magnitude and noise thresholds, thereby enhancing the signal-to-noise ratio without affecting intended audio components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If noise reduction is applied to audio signals, then signal-to-noise ratio is improved, but audio quality and intelligibility may be degraded
Solution Approach 1:
The audio signal is divided into multiple frequency bands (e.g., 0-5kHz, 5-10kHz, 10-15kHz, 15-20kHz) so that noise reduction can be applied selectively to each band based on its characteristics. This allows different attenuation levels for different frequency ranges, preserving important speech frequencies while reducing noise in other bands.
Solution Approach 2:
Different noise reduction strategies are applied to different frequency bands based on their specific characteristics. For example, higher attenuation is applied to frequency bands with lower signal-to-noise ratios, while lower attenuation is applied to bands with higher signal content. This localized approach prevents over-attenuation of important audio components.
2Reliability
If frequency band separation is implemented, then noise reduction effectiveness is improved, but processing complexity increases
Solution Approach 1:
The audio signal is divided into multiple frequency bands using filter banks, which enables targeted noise reduction in each band. This segmentation approach improves noise reduction effectiveness by allowing independent processing of each frequency range based on its specific noise characteristics.
Solution Approach 2:
The system dynamically adjusts processing parameters (such as attenuation factors and threshold values) for each frequency band based on calculated characteristics like envelope differences and signal-to-noise ratios. This adaptive parameter adjustment optimizes noise reduction while managing processing complexity through automated decision-making.
Data Source
AI summary
A computer-implemented method to reduce noise in an audio signal is disclosed. The method may include obtaining an audio signal and separating the audio signal into frequency components in each of multiple frequency bands. The method may include obtaining a first magnitude threshold for a first frequency band of the plurality of frequency bands. The method may include calculating a first envelope of first frequency components in the first frequency band during a first time frame and a second envelope of the first frequency components during a second time frame after the first time frame. The method may include, in response to a difference between the first envelope and the second envelope of the first frequency band being less than the first magnitude threshold, attenuating the first frequency components. The method may include combining the frequency components, including the attenuated first frequency components, to produce an output audio signal.