A study on different linear and non-linear filtering techniques of speech and speech recognition

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ID: 13771
2019
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Abstract
In any signal noise is an undesired quantity, however most of thetime every signal get mixed with noise at different levels of theirprocessing and application, due to which the information containedby the signal gets distorted and makes the whole signal redundant.A speech signal is very prominent with acoustical noises like bubblenoise, car noise, street noise etc. So for removing the noises researchershave developed various techniques which are called filtering. Basicallyall the filtering techniques are not suitable for every application,hence based on the type of application some techniques are betterthan the others. Broadly, the filtering techniques can be classifiedinto two categories i.e. linear filtering and non-linear filtering.In this paper a study is presented on some of the filtering techniqueswhich are based on linear and nonlinear approaches. These techniquesincludes different adaptive filtering based on algorithm like LMS,NLMS and RLS etc., Kalman filter, ARMA and NARMA time series applicationfor filtering, neural networks combine with fuzzy i.e. ANFIS. Thispaper also includes the application of various features i.e. MFCC,LPC, PLP and gamma for filtering and recognition.
Reference Key
haque2019aadbu Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Minajul Haque;Kaustubh Bhattacharyya;
Journal adbu journal of engineering technology
Year 2019
DOI
DOI not found
URL
http://journals.dbuniversity.ac.in/ojs/index.php/AJET/article/download/652/611
Keywords Keywords not found

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