Hearing Instrument Noise Suppression for Stationary Noise and Speech Onsets
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Solution Overview
Problem
Existing hearing instruments face challenges in efficiently and precisely suppressing noise, particularly stationary noise, due to resource-intensive signal processing methods that are not optimized for varying acoustic environments, leading to undesirable comodulation of noise with speech signals.
Innovation Solution
A method for noise suppression in hearing instruments that employs frequency-band-wise noise suppression combined with an analysis that detects both stationary and non-stationary noise, using an artificial neural network (ANN) to set amplification factors based on the detected noise type, ensuring precise noise suppression while preserving speech signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency-band-wise noise suppression is applied to suppress stationary noise, then noise suppression precision is improved, but computational resources and processing complexity increase
Solution Approach 1:
The patent divides the frequency spectrum into multiple frequency bands and applies noise suppression independently to each band. This segmentation allows precise targeted suppression of stationary noise in specific frequency ranges while preserving speech signals in other bands, resolving the contradiction between suppression precision and processing complexity by localizing the computational effort.
Solution Approach 2:
The patent applies different processing characteristics to different frequency bands based on their specific noise conditions. By analyzing noise properties locally in each frequency band and applying band-specific amplification factors, the system achieves high precision noise suppression where needed while maintaining lower processing complexity in bands without stationary noise.
2Reliability
If resource-intensive signal processing methods are used to detect and suppress noise, then noise suppression effectiveness is improved, but energy consumption and computational load increase
Solution Approach 1:
The patent performs preliminary detection of stationary noise characteristics in each frequency band before applying suppression. By pre-identifying noise components and their frequency distributions, the system can apply targeted amplification factors without requiring continuous intensive processing, thus improving effectiveness while reducing ongoing energy consumption.
Solution Approach 2:
The patent applies full noise suppression processing only to frequency bands where stationary noise is detected, while using simpler processing or no processing in bands without stationary noise. This partial application of intensive processing maintains high effectiveness where needed while significantly reducing overall computational energy consumption.
3Object-affected harmful factors
If aggressive noise suppression is applied to remove stationary noise, then noise reduction is improved, but speech signal quality deteriorates due to comodulation
Solution Approach 1:
The patent segments the signal processing into frequency-band-specific operations, allowing aggressive noise suppression to be applied only to bands containing stationary noise while leaving speech-rich bands unaffected. This prevents comodulation artifacts by isolating suppression actions to their appropriate frequency domains.
Solution Approach 2:
The patent dynamically adjusts amplification factors for each frequency band based on detected noise characteristics. By changing the processing parameters (amplification factors) adaptively per band rather than applying uniform suppression, the system achieves effective noise reduction while preserving speech signal quality and avoiding comodulation effects.
Data Source
AI summary
A method for noise suppression in a hearing instrument includes using an acousto-electric input transducer of the hearing instrument to generate an input signal from ambient sound. A frequency-band-wise noise suppression is applied to a processing signal derived from the input signal. Stationary noise is detected in the respective frequency band, and depending on the detected stationary noise, an amplification factor of the processing signal is set for the relevant frequency band. An analysis adapted to detect stationary and non-stationary noise is applied to the processing signal. The analysis has a lower frequency resolution than the frequency-band-wise noise suppression and, upon detected presence of stationary and/or non-stationary noise in the analysis of the processing signal, the stationary noise in the frequency-band-wise noise suppression is presumed to be detected in each frequency band, and the corresponding amplification factors are set.