International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
Speech Enhancement Based on Spectral Subtraction Involving Magnitude and Phase Components Miss Bhagat Nikita 1, Miss Chavan Prajakta 2, Miss Dhaigude Priyanka 3, Miss Ingole Nisha 4, Mr Ranaware Amarsinh 5
Final Year BE Student at College of Engineering Phaltan, Maharashtra, India Final Year BE Student at College of Engineering Phaltan, Maharashtra, India 3 Final Year BE Student at College of Engineering Phaltan, Maharashtra, India 4 Assistant Professor, E&TC Department PES’s College of Engineering, Phaltan, Maharashtra, India 5 Assistant Professor, E&TC Department PES’s College of Engineering, Phaltan, Maharashtra, India 1 2
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distorting speech and thus, the performance of speech enhancement systems is limited between speech distortion and noise reduction. There are several techniques such as Wiener filtering, wavelet-based, adaptive filtering and spectral subtraction is still a useful method. In spectral subtraction method, we have to estimate the noise spectrum and subtract it from noisy speech spectrum. In this method, three following conditions are assumed: (1) the noise is additive (2) speech signal and noise are uncorrelated (3) one channel is available. In this paper, we try to reduce the estimation error of noise spectrum for enhancement of corrupted speech with spectral subtraction technique. We Proposed method has been tested on real speech data by computer simulation in MATLAB environment. Real speech signals from Speech Data database were used for experiments. Then we propose a method to reduce the difference between estimated noise spectrum and noise spectrum.
Abstract - In this paper, we developed a new method to
improve the performance of noisy speech signal by using speech enhancement technique based on single-band spectral subtraction. Spectral subtraction is used to remove noise from noisy speech signals in the frequency domain. This method consists of the spectrum of the noisy speech using the Fast Fourier Transform (FFT) and subtracting the calculated average magnitude of the noise spectrum from the noisy speech spectrum. We applied spectral subtraction to the noisy speech signal. The denoise algorithm was implemented using Matlab software by storing the noisy speech data into half overlapped (overlap add processing) and calculate the corresponding magnitude spectrum using the FFT, removing the noise from the noisy speech, and reconstructing the speech back into the time do-main using the inverse Fast Fourier Transform (IFFT). Key Words: Speech Enhancement, Spectral subtraction, FFT, Noise Estimation, overlap add processing, IFFT.
1.1 Single Channel Speech Enhancement 1.Introdction
In general, single channel systems constitute by depending on different statistics of speech and unwanted noise that, work in most difficult situations where no prior knowledge of noise is available. Usually the methods assume that the noise is stationary when speech is active. They normally allow non-stationary noise between speech activity periods but in reality, when the noise is non-stationary, the performance of speech signal is dramatically decreases.
In speech enhancement, the number of noise are added into original clean speech signal. There are number of methods to remove noise signal. Telephones are increasingly being used in noisy environments such as cars, airports, streets, trains, station. So, we try to remove the noise using spectral subtraction method. The aim of this project is to implement a real-time system that will reduce the background noise in a speech signal. This process is called speech enhancement. In many speech communication systems, background noise causes the quality of speech to degrade. In most of speech processing applications such as mobile communications, speech recognition and hearing aids removing the back- ground noise in a noisy environment is inevitable. So, speech enhancement as a necessity for related applications has been widely studied in recent years. The main objective of speech enhancement is to reduce the noise from noisy speech, such as the speech quality or intelligibility. It is usually difficult to reduce noise without
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1.2 Spectral Subtraction Basic Many different algorithms have been developed for speech enhancement: the one that we use is known as spectral subtraction algorithm. This technique operates in the frequency domain and makes the assumption that the spectrum of the input signal can be expressed as the sum of the speech spectrum and the noise spectrum. The procedure is illustrated in the diagram below and contains two important parts:
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