Multimodal biometrics using multiple feature representations to speaker identification system

Rami Al-Hmouz, Khaled Daqrouq, Ali Morfeq, Witold Pedrycz

نتاج البحث

3 اقتباسات (Scopus)

ملخص

Multimodal biometrics combines information coming from multiple biometrics with a key objective to reduce the limitations associated with any single biometric method such as low accuracy, limited security, noisy measurements, etc. In this study, different multimodal speaker identification approaches are investigated. Linear predictive coding features, Mel-frequency cepstral coefficients features, discrete wavelet based linear predictive coding features are examined with the use of different combinations of features applied to the identification system. In building the multimodal system, fusion is realized at the score level using Gaussian mixture model. The system is tested on publicly available data set and shows improvement in the classification rate for all feature extraction methods.

اللغة الأصليةEnglish
عنوان منشور المضيف2015 International Conference on Information and Communication Technology Research, ICTRC 2015
ناشرInstitute of Electrical and Electronics Engineers Inc.
الصفحات314-317
عدد الصفحات4
رقم المعيار الدولي للكتب (الإلكتروني)9781479989669
المعرِّفات الرقمية للأشياء
حالة النشرPublished - يوليو 14 2015
الحدث1st International Conference on Information and Communication Technology Research, ICTRC 2015 - Abu Dhabi
المدة: مايو ١٧ ٢٠١٥مايو ١٩ ٢٠١٥

سلسلة المنشورات

الاسم2015 International Conference on Information and Communication Technology Research, ICTRC 2015

Other

Other1st International Conference on Information and Communication Technology Research, ICTRC 2015
الدولة/الإقليمUnited Arab Emirates
المدينةAbu Dhabi
المدة٥/١٧/١٥٥/١٩/١٥

ASJC Scopus subject areas

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