01594nas a2200145   4500008004100000245006900041210006700110260001200177300001000189490000700199520114200206100002101348700003201369856004701401       2023                        eng d00aASR Features Extraction Using MFCC And LPC: A Comparative Study-0 aASR Features Extraction Using MFCC And LPC A Comparative Study  c06/2023  a39-490 v213 a<p>The field of Automatic Speaker Recognition (ASR) is an important and open field for researchers and scientists, especially as it has become essential in facilitating the work we do in our daily lives. Such as digital authentication and electronic transactions, and consider It as a secure environment to authenticate users' access to their accounts. Many technologies have been developed in the field of recognition but so far, there is no complete tool or method for speaker identification, the most important step in ASR is the extraction of voice features. Many methods and tools can be used to extract the speaker’s vocal characteristics (voice features), which in turn will identify the user and recognize his voice spectrum through the phonetic linguistic message. In this paper, two methods will be studied, each using a different technique MFCC, which uses a logarithmic scale, and LPC, which uses a linear scale. The method used in ASR should have minimal error because it is an important authentication technology like a fingerprint, where two different people cannot have the same voice spectral range (voiceprint).</p>
1 aAlkhatib, Bassel1 aEddin, Mohammad, Madian Kam  uhttp://www.dline.info/download.php?sn=3757