An Improved Speech Enhancement Algorithm Based on Wiener-Filtering

2014 ◽  
Vol 989-994 ◽  
pp. 2565-2568
Author(s):  
Yu Hong Liu ◽  
Dong Mei Zhou ◽  
Jing Di
Keyword(s):  
Real Time ◽  
Speech Enhancement ◽  
Moving Average ◽  
Wiener Filtering ◽  
Signal Distortion ◽  
Noise Elimination ◽  
Speech Distortion ◽  
Spectrum Shaping ◽  
Enhancement Algorithm ◽  
Real Time Application

This paper proposes an improved speech enhancement algorithm based on Wiener-Filtering, which addresses the problems of speech distortion and musical noise. The proposed algorithm adopts the masking properties of human auditory system on calculating the gain of spectrum point, in order that the signal in the enhanced speech whose energy is lower than the threshold will not be decreased further and the less distortion will be brought to enhanced speech by the trade-off between the noise elimination and speech signal distortion. What’s more, in order to eliminate the “musical noise”, a spectrum-shaping technology using averaging method between adjacent frames is adopted. And to guarantee the real-time application, two-stage moving-average strategy is adopted. The computer simulation results show that the proposed algorithm is superior to the traditional Wiener method in the low CPU cost, real-time statistics, the reduction of the speech distortion and residual musical noise.

Speech Intelligibility Enhancement Using Distortion Control

2014 ◽  
Vol 912-914 ◽  
pp. 1391-1394
Author(s):  
Yu Xiang Yang ◽  
Jian Fen Ma
Keyword(s):  
Noise Reduction ◽  
Speech Enhancement ◽  
Speech Intelligibility ◽  
Signal Distortion ◽  
Gain Function ◽  
Noisy Speech ◽  
Speech Distortion ◽  
Distortion Control ◽  
Enhancement Algorithm

In order to improve the intelligibility of the noisy speech, a novel speech enhancement algorithm using distortion control is proposed. The reason why current speech enhancement algorithm cannot improve speech intelligibility is that these algorithms aim to minimize the overall distortion of the enhanced speech. However, different speech distortions make different contributions to the speech intelligibility. The distortion in excess of 6.02dB has the most detrimental effects on speech intelligibility. In the process of noise reduction, the type of speech distortion can be determined by signal distortion ratio. The distortion in excess of 6.02dB can be properly controlled via tuning the gain function of the speech enhancement algorithm. The experiment results show that the proposed algorithm can improve the intelligibility of the noisy speech considerably.

scholarly journals A RED modified weighted moving average for soft real-time application

2014 ◽  
Vol 24 (3) ◽  
pp. 697-707 ◽  
Author(s):  
Joanna Domanśka ◽  
Adam Domański ◽  
Dariusz R. Augustyn ◽  
Jerzy Klamka
Keyword(s):  
Real Time ◽  
Optimization Problem ◽  
Optimality Criterion ◽  
Task Force ◽  
Moving Average ◽  
Timing Constraints ◽  
Real Time Traffic ◽  
Real Time Application ◽  
Weighted Moving Average

Abstract The popularity of TCP/IP has resulted in an increase in usage of best-effort networks for real-time communication. Much effort has been spent to ensure quality of service for soft real-time traffic over IP networks. The Internet Engineering Task Force has proposed some architecture components, such as Active Queue Management (AQM). The paper investigates the influence of the weighted moving average on packet waiting time reduction for an AQM mechanism: the RED algorithm. The proposed method for computing the average queue length is based on a difference equation (a recursive equation). Depending on a particular optimality criterion, proper parameters of the modified weighted moving average function can be chosen. This change will allow reducing the number of violations of timing constraints and better use of this mechanism for soft real-time transmissions. The optimization problem is solved through simulations performed in OMNeT++ and later verified experimentally on a Linux implementation

A Higher Intelligibility Speech-Enhancement Algorithm

2013 ◽  
Vol 321-324 ◽  
pp. 1075-1079
Author(s):  
Peng Liu ◽  
Jian Fen Ma
Keyword(s):  
Speech Enhancement ◽  
Speech Intelligibility ◽  
Minimum Mean Square Error ◽  
A Priori ◽  
Objective Evaluation ◽  
Mean Square ◽  
Magnitude Spectrum ◽  
Gain Matrix ◽  
Speech Distortion ◽  
Enhancement Algorithm

A higher intelligibility speech-enhancement algorithm based on subspace is proposed. The majority existing speech-enhancement algorithms cannot effectively improve enhanced speech intelligibility. One important reason is that they only use Minimum Mean Square Error (MMSE) to constrain speech distortion but ignore that speech distortion region differences have a significant effect on intelligibility. A priori Signal Noise Ratio (SNR) and gain matrix were used to determine the distortion region. Then the gain matrix was modified to constrain the magnitude spectrum of the amplification distortion in excess of 6.02 dB which damages intelligibility much. Both objective evaluation and subjective audition show that the proposed algorithm does improve the enhanced speech intelligibility.

Improved Spectral Subtraction Speech Enhancement Algorithm

2013 ◽  
Vol 760-762 ◽  
pp. 536-541 ◽  
Author(s):  
Yu Hong Liu ◽  
Dong Mei Zhou ◽  
Zhan Jun Jiang
Keyword(s):  
Auditory System ◽  
Speech Enhancement ◽  
Critical Frequency ◽  
Spectral Subtraction ◽  
Human Auditory System ◽  
Speech Distortion ◽  
Simulation Results ◽  
Enhancement Algorithm ◽  
Output Snr

The paper addresses the problems of speech distortion and residual musical noise introduced by conventional spectral subtraction (SS) method for speech enhancement. In this paper, we propose a modified SS algorithm for speech enhancement based on the masking properties of human auditory system. The algorithm computes the parameters α and β dynamically according to the masking thresholds of the critical frequency segments for each speech frame. Simulation results show that the proposed algorithm is superior to the conventional SS method, not only in the improvement of output SNR, but in the reduction of the speech distortion and residual musical noise.

Real-time speech enhancement algorithm for transient noise suppression

2020 ◽  
Author(s):  
Ruiyu Liang ◽  
Yue Xie ◽  
Jiaming Cheng ◽  
Guichen Tang ◽  
Shinuo Sun
Keyword(s):  
Real Time ◽  
Speech Enhancement ◽  
Noise Suppression ◽  
Enhancement Algorithm
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