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Acoustic Feature Extraction and Optimized Neural Network based Classification for Speaker Recognition
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
Identifying the person from his or her voice characteristics is an essential trait for human interaction. Automatic speaker recognition (ASR) systems are developed to find the identity of the speaker in the field of forensics, business interactions and law enforcement. It can be achieved by extracting prosodic, linguistic, and acoustic speech characteristics. Furthermore optimized neural network based approaches are reviewed to classify the extracted features. In this paper, literatures are
doi:10.35940/ijitee.i7760.078919
fatcat:r2ku2ubwyrejto22ayagljepvy