A Speech Enhancement Algorithm Based on the “Music Noise” Analysis

2014 ◽  
Vol 543-547 ◽  
pp. 2784-2787
Author(s):  
Ying Ma ◽  
Xiao Hua Zhang ◽  
Bing Lei Xing
Keyword(s):  
Speech Enhancement ◽  
Noise Analysis ◽  
Noise Pollution ◽  
Spectral Subtraction ◽  
Voice Communication ◽  
Spectrum Correction ◽  
Spectral Subtraction Method ◽  
The Voice ◽  
Enhancement Algorithm ◽  
Communication Equipment

Interference is inevitable process of voice communication will be from the surrounding environment and transmission medium noise, communication equipment, electronic noise, and other speakers. These interference makes the voice receiver received for noisy speech signal with noise pollution. According to the traditional spectral subtraction residual musical noise is too strong, the weighted processing is reduced and the power spectrum correction, spectral subtraction method was adopted to improve the traditional. According to the analysis of real speech data collection simulation, improved spectral subtraction can effectively reduce the musical noise, can satisfy the requirement of speech enhancement.

An Improved Spectral Subtraction Algorithm Study Based on Voice Human-Computer Interaction in Cockpit

2010 ◽  
Vol 139-141 ◽  
pp. 2154-2157
Author(s):  
Ji Xiang Lu ◽  
Ping Wang ◽  
Long Yi
Keyword(s):  
Speech Recognition ◽  
Human Computer Interaction ◽  
Speech Enhancement ◽  
Spectral Subtraction ◽  
Masking Effect ◽  
Auditory Masking ◽  
Speech Output ◽  
Voice Interaction ◽  
Speech Information ◽  
The Voice

The voice interaction in cockpit mainly includes speech recognition, enhancement and synthesis. This interaction transfers the speech information to the corresponding orders to make machines in cockpit work unmistaken, also feedback the execution results to users by speech output devices or some other ways. The speech enhancement technology is studied in this paper, aiming at the Voice Interactive. We propose an improved spectral subtraction (SS) algorithm based on auditory masking effect, by using two steps SS. The simulated results based on the segment SNR compared to the traditional SS show the effectiveness and superiority of the improved algorithm.

scholarly journals The Application of Nonlinear Spectral Subtraction Method on Millimeter Wave Conducted Speech Enhancement

2010 ◽  
Vol 2010 ◽  
pp. 1-12 ◽  
Author(s):  
Sheng Li ◽  
Jian Qi Wang ◽  
Xi Jing Jing
Keyword(s):  
Millimeter Wave ◽  
Speech Enhancement ◽  
Spectral Subtraction ◽  
Frequency Noise ◽  
Distribution Analysis ◽  
Subtraction Method ◽  
Time Frequency ◽  
Perceptual Evaluation ◽  
Reduction Effect ◽  
Spectral Subtraction Method

A nonlinear multiband spectral subtraction method is investigated in this study to reduce the colored electronic noise in millimeter wave (MMW) radar conducted speech. Because the over-subtraction factor of each Bark frequency band can be adaptively adjusted, the nonuniform effects of colored noise in the spectrum of the MMW radar speech can be taken into account in the enhancement process. Both the results of the time-frequency distribution analysis and perceptual evaluation test suggest that a better whole-frequency noise reduction effect is obtained, and the perceptually annoying musical noise was efficiently reduced, with little distortion to speech information as compared to the other standard speech enhancement algorithm.

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.

scholarly journals An Iterative Graph Spectral Subtraction Method for Speech Enhancement

2020 ◽  
Vol 123 ◽  
pp. 35-42
Author(s):  
Xue Yan ◽  
Zhen Yang ◽  
Tingting Wang ◽  
Haiyan Guo
Keyword(s):  
Speech Enhancement ◽  
Spectral Subtraction ◽  
Subtraction Method ◽  
Spectral Subtraction Method
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