The effect of the additivity assumption on time and frequency domain wiener filtering for speech enhancement

2007 ◽  
Author(s):  
Kamil K. Wójcicki ◽  
Stephen So ◽  
Kuldip K. Paliwal
Keyword(s):  
Frequency Domain ◽  
Speech Enhancement ◽  
Wiener Filtering

scholarly journals Wiener Filtering in Frequency Domain to Enhance Speech Corrupted by Colored Noise

2019 ◽  
Vol 8 (2S11) ◽  
pp. 1058-1062
Keyword(s):  
Frequency Domain ◽  
Performance Measures ◽  
Speech Enhancement ◽  
Colored Noise ◽  
Quality Measures ◽  
Wiener Filtering ◽  
Spectral Distortion ◽  
Gain Function ◽  
Objective Quality ◽  
Log Likelihood

This paper presents a method for speech enhancement to predict speech quality in presence of highly non-stationary scenarios using basic wiener filtering in frequency domain with an adaptive gain function under eight different noises at three different ranges of input SNR. Its performance is evaluated in terms of objective quality measures like LPC based spectral distortion measures are Cepstrum Distance, Itakura Saito and Log Likelihood Ratio. This method was tested using Noizeous database, its performance measures were compared against spectral subtractive type algorithms and it shows its improvements in terms of objective quality measures.

Subspace and Frequency Domain Speech Enhancement Techniques

2021 ◽  
Author(s):  
Ragipati Naga Sai Tejaswini ◽  
Ravi Kumar Kandagatla ◽  
Jahnavi Nandeti ◽  
Mamidi Krupakar ◽  
Paragati Haveela
Keyword(s):  
Frequency Domain ◽  
Speech Enhancement
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