Implementation of Spectral Subtraction Using Sub-band Filtering in DSP C6748 Processor for Enhancing Speech Signal

2018 ◽  
pp. 259-267
Author(s):  
U. Purushotham ◽  
K. Suresh
Keyword(s):  
Speech Signal ◽  
Spectral Subtraction

Nonlinear Spectral Subtraction Method for Elimination of Aircraft Engine’s Noise from Degraded Speech Signals

2011 ◽  
Vol 130-134 ◽  
pp. 1327-1330
Author(s):  
Xiu Ying Zhao ◽  
Hong Yu Wang ◽  
Shou Yu Tong ◽  
De You Fu ◽  
Hai Shen Zhou
Keyword(s):  
Frequency Spectrum ◽  
Speech Signal ◽  
The Other ◽  
Spectral Subtraction ◽  
Subtraction Method ◽  
Nonlinear Method ◽  
Input Noise ◽  
Degraded Speech ◽  
Main Input ◽  
Spectral Subtraction Method

The spectral subtraction is one of the best methods for elimination of approximate cyclical engine’s noise from degraded speech signal. Here we turn to research about the nonlinear spectral subtraction method and its improved model. After studying the nonlinear method we turn to this method that whether it can improve the quality of enhanced speech signal, propose the short-time spectral subtraction, which needs two inputs. The main input is containing the voice that is corrupted by noise. The other input (noise reference input) contains noise related in some way to that of the main input (background noise). Then use the main input’s frequency spectrum subtract the other input’s frequency spectrum. The results of experiment have proved it’s effective.

Application of the Speech Enhancement Technology in Flight Simulation System

2014 ◽  
Vol 556-562 ◽  
pp. 3408-3411
Author(s):  
Jing Xin Xiao ◽  
Lin Deng ◽  
Yun He ◽  
You Yi Li
Keyword(s):  
Speech Enhancement ◽  
Speech Processing ◽  
Speech Signal ◽  
Research Team ◽  
Simulation System ◽  
Flight Simulation ◽  
Spectral Subtraction ◽  
Enhancement Technology ◽  
Interrupted Speech

Speech signal can be effect by the external interruption in the process of flight simulation, which results in the deteriorated speech processing performance in flight simulation system. To solve the problem, speech enhancement module has been developed using the spectral subtraction algorithm based on the flight simulation system developed by the research team. The module will improve the recognition rates and provide advanced anti-jam capabilities for the speech processing performance of the flight simulation system. The feasibility and validity of this speech enhancement module is validated by processing the interrupted speech signal. The work in this paper has laid foundation for the application of the speech enhancement technology in flight simulation system.

scholarly journals Noise Reduction from Speech Signals using Modified Spectral Subtraction Technique

2018 ◽  
Vol 3 (7) ◽  
pp. 78
Author(s):  
Chowdhury Shahriar Muzammel ◽  
Mahmudul Hasan ◽  
Khalil Ahammad ◽  
Mousumi Hasan Mukti
Keyword(s):  
White Noise ◽  
Noise Reduction ◽  
Speech Signal ◽  
Gaussian White Noise ◽  
Research Work ◽  
Spectral Subtraction ◽  
Experimental Result ◽  
Subtraction Method ◽  
Color Noise ◽  
Spectral Subtraction Method

Varieties of environmental sources of noise and distortion can degrade the quality of the speech signal in a communication system. This research work explores the effects of these interfering sounds on speech applications and introduces a technique for reducing their influence and enhancing the acceptability and intelligibility of the speech signal. In this work, a noise reduction system using single microphone method in time domain to improve SNR of noise contaminated speech is proposed. Traditional Spectral Subtraction method has been reviewed very well and the relationship with wiener filter is also illustrated. The Spectral Subtraction method has been generalized and the focus is put on reducing noise from speech in single channel signals. Voice Activity Detector (VAD) is ignored in this proposed system, because a-priori information about the noise is assumed. The research has been conducted using Gaussian White Noise and Color Noise. The experimental result shows a remarkable improvement in SNR for the generalized version and it is noticed that the result is very much satisfactory when white noises are added but the addition of color noise produces a comparatively poor improvement report. The system has been tested with eight different datasets and on an average, 65.27% improvement in SNR (Signal to Noise Ratio) for White Noise using Generalized Spectral Subtraction Method is achieved comparing with Traditional Spectral Subtraction Method. The average improvement in SNR for Color Noise recorded is 53.31%. The Generalized Spectral Subtraction method is shown to improve the speech quality and to improve SNR as well.

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