Implementation of Modified Wiener Filtering in Frequency Domain in Speech Enhancement

Abstract

The most common complaint about Digital Hearing Aids is feedback noise. Many attempts have been undertaken in recent years to successfully reduce feedback noise. A wiener filter, which calculates the wiener gain using before and after filtering SNR, is one technique to reduce background noise. Modified Noise Reduction Method (MNRM), a new way for reducing feedback noise Reduction, is presented in this work. In the Modified Noise Reduction Strategy, the advantages of a wiener filter are merged with a decision-directed approach and a twin-stage noise suppression technique The Modified Noise Reduction method can reduce the noise more successfully, according to comprehensive MATLAB programming, investigation, and findings analysis. After being modelled in MATLAB for seven distinct noise types, the SNR of the two architectures is compared.

Multi-Channel Speech Enhancement using a Minimum Variance Distortionless Response Beamformer based on Graph Convolutional Network

“…With some missing information about the dataset configurations and the authors did not publish the implementation of their proposed model in [23], we decided to utilize the dataset provided from ConferencingSpeech 2021 Challenge [25] [65], AISHELL-3 4 [66], and Librispeech [67]. The speech utterances with SNR higher than 15 dB are selected for training.…”

“…Speech enhancement is a subject studied and applied in many applications, e.g., automatic speech recognition, teleconference, or aided hearing [1][2][3][4]. There are two algorithm categories of speech enhancement: single-channel algorithms (using a single microphone) [5][6][7][8] and multi-channel algorithms (using multi microphones) [9], [10].…”