Volume 7 Issue 1 - May 2016

  • 1. Noise reduction using kalman filter

    Authors : Gaurav Badhwar , Dr. Amandeep Singh Sappal

    Pages : 639-643

    DOI : http://dx.doi.org/10.21172/1.71.091

    Keywords : Kalman filter, Speech enhancement, Speech communication, Additive white noise

    Abstract :

    In speech communication systems, it is found that speech signals easily get affected by noise and tamper the system accuracy and performance. Before processing a speech signal, it is very important to filter out the noise from corrupted speech signal to enhance the accuracy and the performance of communication systems. It is also important to enhance the quality of the speech and also to enhance the listening ability. But in practice, it is very complicated to filter out the noise from the desired speech signal to obtain noise free speech signal all time for the speech communication system. In the last few years, several speeches filtering algorithms have been introduced in order to filter out the noise from the desired speech signal. In this paper, the problem of speech enhancement is discussed when a corrupted speech signal with an additive white noise is the only information available for processing. The main idea of the paper is to use the Kalman filtering technique to estimate the future clean samples from the first one in an iterative way. The simulation uses mean square error as a tool to realize the similarity and minimum errors between estimated signal and true signal.

    Citing this Journal Article :

    Gaurav Badhwar , Dr. Amandeep Singh Sappal, "Noise reduction using kalman filter", https://www.ijltet.org/journal_details.php?id=901&j_id=3107, Volume 7 Issue 1 - May 2016, 639-643, #ijltetorg