A new speech intelligibility improvement method for near-end listening enhancement in noisy environments is proposed. This method improves speech intelligibility by optimizing energy correlation of one-third octave bands of clean speech and enhanced noisy speech without More
A new speech intelligibility improvement method for near-end listening enhancement in noisy environments is proposed. This method improves speech intelligibility by optimizing energy correlation of one-third octave bands of clean speech and enhanced noisy speech without power increasing. The energy correlation is determined as a cost function based on frequency band gains of the clean speech. Interior-point algorithm which is an iterative procedure for the nonlinear optimization is used to determine the optimal points of the cost function because of nonlinearity and complexity of the energy correlation function. Two objective intelligibility measures, speech intelligibility index and short-time objective intelligibility measure, are employed to evaluate the noisy enhanced speech intelligibility. Furthermore, the speech intelligibility scores are compared with unprocessed speech and a baseline method under various noisy conditions. The results show large intelligibility improvements with the proposed method over the unprocessed noisy speech.
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Speech enhancement aims to improve the quality and intelligibility of speech using various techniques and algorithms. The speech signal is always accompanied by background noise. The speech and communication processing systems must apply effective noise reduction techni More
Speech enhancement aims to improve the quality and intelligibility of speech using various techniques and algorithms. The speech signal is always accompanied by background noise. The speech and communication processing systems must apply effective noise reduction techniques in order to extract the desired speech signal from its corrupted speech signal. In this project we study wavelet and wavelet transform, and the possibility of its employment in the processing and analysis of the speech signal in order to enhance the signal and remove noise of it. We will present different algorithms that depend on the wavelet transform and the mechanism to apply them in order to get rid of noise in the speech, and compare the results of the application of these algorithms with some traditional algorithms that are used to enhance the speech. The basic principles of the wavelike transform are presented as an alternative to the Fourier transform. Or immediate switching of the window The practical results obtained are based on processing a large database dedicated to speech bookmarks polluted with various noises in many SNRs. This article tends to be an extension of practical research to improve speech signal for hearing aid purposes. Also learn about the main frequency of letters and their uses in intelligent systems, such as voice control systems.
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