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- W2467206671 abstract "Kurukshetra University, Department of Instrumentation & Control Engineering., H.E.C* Jagadhri, Haryana, 135003, India sachdevaanjali26@gmail.com ABHIJEET KUMAR Mullana University, Department of Electronics and Comm. Engineering., M.M.E.C Mullana, Haryana, 133203, India abhijeetsliet@gmail.com NIDHIKA BIRLA Kurukshetra University, Department of Electronics Engineering., H.E.C Jagadhri, Haryana, 135003, India nidhikabirla@gmail.com Abstract: The Voice is a signal of infinite information. Digital processing of speech signal is very important for high-speed and precise automatic voice recognition technology. Nowadays it is being used for health care, telephony military and people with disabilities therefore the digital signal processes such as Feature Extraction and Feature Matching are the latest issues for study of voice signal. In order to extract valuable information from the speech signal, make decisions on the process, and obtain results, the data needs to be manipulated and analyzed. Basic method used for extracting the features of the voice signal is to find the Mel frequency cepstral coefficients. Mel-frequency cepstral coefficients (MFCCs) are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency.This paper is divided into two modules. Under the first module feature of the speech signal are extracted in the form of MFCC coefficients and in another module the non linear sequence alignment known as Dynamic Time Warping (DTW) introduced by Sakoe Chiba has been used as features matching techniques. Since it’s obvious that the voice signal tends to have different temporal rate, the alignment is important to produce the better performance. This paper presents the feasibility of MFCC to extract features and DTW to compare the test patterns." @default.
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- W2467206671 date "2010-01-01" @default.
- W2467206671 modified "2023-09-24" @default.
- W2467206671 title "VOICE COMMAND RECOGNITION SYSTEM BASED ON MFCC AND DTW" @default.
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