Beschreibung
Automatic identification of different voice qualities present in a speech signal which is very beneficiary for detecting any kind of speech by an efficient speech recognition system. Proposed technique is based on three important characteristics of speech signal namely Zero Crossing Rate, Short Time Energy and Fundamental Frequency. The performance of the proposed algorithm is evaluated using the data collected from three different speakers and an overall accuracy of 87.2 % is achieved.
Autorenporträt
Born Kurusketra (Haryana) 22nd March 1989. B.Tech (CS) from Kurukshetra Univeristy, M.tech (CSA) Thapar University. Currently working as Assistant professor in Amity University Gurgaon, Area of interest includes NLP, data analytics, machine learning.
Herstellerkennzeichnung:
OmniScriptum SRL
Str. Armeneasca 28/1, office 1
2012 Chisinau
MD
E-Mail: info@omniscriptum.com
