Automatic Speaker Recognition using Mel Frequency Cepstral Coefficients (MFCC) and Fast Fourier Transform (FFT)

dc.contributor.authorAMEUR Nehal
dc.contributor.authorENCA/ Dr. KHENNOUF Salah
dc.date.accessioned2026-01-04T09:59:58Z
dc.date.available2026-01-04T09:59:58Z
dc.date.issued2025
dc.description.abstractThis work focuses on automatic speaker verification identity via his voice, which is a recent task of the Automatic Speaker Recognition field. This work is divided into two phases: The first phase "called training or learning phase" consists of acquiring and saving audio recordings of a group of speakers into PC. In the second phase "testing phase", an anonymous speech is introduced and compared its characteristics with the characteristics of previous recordings, using a set of algorithms (such as: MFCC, FFT) to make a decision. The speech files that were recorded and processed in this work are obtained using a personal computer microphone instead of special equipment, which explains the weakness of the obtained results.
dc.identifier.urihttps://repository.univ-msila.dz/handle/123456789/48083
dc.language.isoen
dc.publisherUniversity of Msila
dc.titleAutomatic Speaker Recognition using Mel Frequency Cepstral Coefficients (MFCC) and Fast Fourier Transform (FFT)
dc.typeThesis

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