Abstract
In this paper, we propose a single-channel speech enhancement method in terms of subspace techniques to reduce the noises from speech signals in various noises environment. This subspace approach based on Karhunen-Loeve transform and implemented via Principal component analysis. The optimal subspace selection is provided by a minimum description length criterion. An offset factor generated from the white noise was used to modify the variance to adapt to the specified colored noise. Several objective speech quality measures have been introduced to give an overall evaluation of the proposed method. A large amount of data and figures, as well as the audio quality evaluation results, testify that the algorithm provides high performance for the input signal-to-noise ratio range from -5dB to 10dB. It is showed that the proposed approach have excellent characteristics for colored noises in strong background noise environment with lower signal-to-noise ratio. DOI: http://dx.doi.org/10.11591/telkomnika.v11i2.1999
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: TELKOMNIKA Indonesian Journal of Electrical Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
