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Improved Speaker Recognition over VoIP using Auditory Features | IEEE Conference Publication | IEEE Xplore

Improved Speaker Recognition over VoIP using Auditory Features


Abstract:

This work presents a novel framework based on a discriminative auditory feature extractor for speaker recognition over VoIP network. The auditory model that simulates the...Show More

Abstract:

This work presents a novel framework based on a discriminative auditory feature extractor for speaker recognition over VoIP network. The auditory model that simulates the mid-external and inner ear is incorporated into the conventional Mel Frequency Cepstral Coefficients (MFCC) scheme to produce new parameters that we named Ear Frequency Cepstral Coefficients (EFCCs). The experiments are conducted on the TIMIT corpus and the EFCC, used as input parameters tothe i-vector algorithm. Results showed interesting performances compared to the conventional MFCC parameters. In addition, this improvement was obtained by using fewer parameters (43 EFCCs vs 60 MFCCs) in our experiment.
Date of Conference: 28 October 2018 - 01 November 2018
Date Added to IEEE Xplore: 17 January 2019
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Conference Location: Aqaba, Jordan

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