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|Title:||NOISE REDUCTION IN SPEECH ENHANCEMENT BY SPECTRAL SUBTRACTION WITH SCALAR KALMAN FILTER|
|Authors:||Đặng Minh, Công|
|Abstract:||In the system that related to speech communication like telecommunication system or speech processing, the presence of background noise in speech signal is undesirable. Background noise can make the user harder to hear the speech, or decrease the performance of speech processing systems. Therefore, to enhance the quality of speech signal, noise reduction is an important problem. In this thesis, we present a single channel noise reduction method for speech enhancement. This method is based on the principle of spectral subtraction methods, with the addition of using scalar Kalman Filter for residual noise removal. It models the changing of speech magnitude spectrum as Gaussian random process and the magnitude residual noise as Gaussian white noise for applying scalar Kalman Filter. The scalar Kalman Filter used in this method is designed in order to be suitable for the characteristics of speech and noise signal. Our obtained experiment results with the online NOIZEUS speech corpus show that the presented method has consistent improved the SNR measures of noisy speech signal. In overall, experiment results also show that the SNR improvement of the presented method is better than other basic implementations of spectral subtraction.|
|Appears in Collections:||Khóa luận Khoa Vật lý kỹ thuật và Công nghệ Nano|
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