Spectrogram Enhanced Pitch Period Tracking using MWSG Filter in Noisy Environments
T. Balasri Sathakarni1, B. Leela Kumari2
1T. Balasri Sathakarni, Department of Engineering and Communication Engineering, University College of Engineering, JNTUK, Kakinada, India.
2Dr. B. Leela Kumari, Department of Engineering and Communication Engineering, University College of Engineering, JNTUK, Kakinada, India.
Manuscript received on 12 March 2019 | Revised Manuscript received on 18 March 2019 | Manuscript published on 30 July 2019 | PP: 5426-5428 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3542078219/19©BEIESP | DOI: 10.35940/ijrte.B3542.078219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Speech Processing is the study of speech signals which carry individual information such as speaker characteristics, acoustic environment, etc due to which the parameters defining the signal are unique. Pitch Period, Duration, Intensity are the parameters that play the main role in coding speech applications such as authentication, surveillance, speaker recognition. As the conventional filters are static in nature, for non-linear and non-stationary variations of signal parameters adaptive filtering models which are robust are required. Hence the tracking and estimation of the parameters can be done by using Particle-Kalman Filter. It is very important that the signal has to track perfectly even in the presence of noise, by removing the noise and thereby enhancing the output. The approach in this paper is to propose a method for enhancing the performance, using multiple window Savitzky-Golay Filter (MWSG Filter). The performance of filter is measured by parameters Viz., SNR and PSNR.
Index Terms: Kalman Filter, MWSG Filter, Particle Filter, Pitch Period.
Scope of the Article: Machine-to-Machine Communications for Smart Environments