ASR Features Extraction Using MFCC and LPC: A Comparative Study-

TitleASR Features Extraction Using MFCC and LPC: A Comparative Study-
Publication TypeJournal Article
Year of Publication2022
AuthorsEddin, MMadian Kam, Alkhatib, B
JournalJournal of Digital Information Management
Volume20
Issue3
Start Page79
Pagination79-89
Date Published09-2022
Type of ArticleResearch
Abstract

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. Many technologies have been developed in the recognition field. Such as digital authentication and electronic transactions; consider It a secure environment to authenticate user's access to their accounts. Still, so far, there is no complete tool or method for speaker identification, the most crucial step in ASR is the extraction of voice features. Many techniques and tools can extract the speaker's vocal characteristics (voice features), identifying the user and recognising his voice spectrum through the phonetic and 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 a minimal error because it is a crucial authentication technology like a fingerprint, where two different people cannot have the same voice spectral range (voiceprint).

URLhttp://www.dline.info/download.php?sn=3566
DOI10.6025/jdim/2022/20/3/79-89
Refereed DesignationRefereed

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Institute of Electronic and Information Technology (IEIT)

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