Open AccessSpectrogram Enhanced Pitch Period Tracking using MWSG Filter in Noisy Environments
Author(s) -
T.Balasri Sathakarni,
Dr.B.Leela Kumari
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3542.078219
Subject(s) - spectrogram , computer science , speech recognition , filter (signal processing) , adaptive filter , noise (video) , signal (programming language) , filter design , kalman filter , pitch detection algorithm , acoustics , speech processing , artificial intelligence , algorithm , computer vision , image (mathematics) , physics , programming language
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