A novel approach for design of a speech enhancement system using auto-trained NLMS adaptive filter Online publication date: Sat, 26-Jul-2014
by Sivaranjan Goswami; Bijeet Bardoloi; Pinky Deka; Darathi Dutta; Dipjyoti Sarma
International Journal of Information and Communication Technology (IJICT), Vol. 6, No. 3/4, 2014
Abstract: Speech signal often gets degraded by various types of noise at different stages of speech signal operations. One major type of noise is the background noise which is the acoustic sound waves from various sources that disrupt the original signal. Adaptive filters are found to be very reliable and effective in speech enhancement. However, one major problem is training. For training, we must have a priori knowledge of the noise-free speech. But practically, it is not possible to have a priori knowledge of the speech that has been recorded in a particular background. The work here proposes an adaptive filter-based algorithm for enhancement of the noisy speech. The only requirement is any clean short voice record of the same speaker. The work proposed here increases the output SNR by around 1.5 times the input SNR and also enhances the listening comfort of the speech.
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