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Details for article 50 of 160 found articles
| Title: |
Contribution to the Vocal Print Recognition in Arabic Language |
| Author: |
Abdennaceur Kachouri Tarak Hdiji Zied Sakka Mounir Samet |
| Appeared in: |
Journal of applied sciences |
| Paging: | Volume 7 (2007) nr. 18 pages 2560-2567 |
| Year: |
2007 |
| Contents: |
The study presents a new database dedicated to speaker recognition applications. The main characteristics of this Arabic database are spoken by native and non-native speakers, a single session of sentence reading and relatively extensive speech samples suitable for learning person specific speech characteristics. This speech database is dedicated to the modelling and the representation of speakers. The representation consists in extracting parameters (MFCC: Mel Frequency Cepstral Coefficients or LPCC: Linear Prediction Cepstral Coefficients) that characterize the voice or a speaker`s vocal print from isolated words either linked from the Arabic database prepared for this work. The technique used in the phase of recognition adapted to this type of data and that showed more performance is the one of HMM (Hidden Markov Models). One tidy preparation of the training database and a good choice of entrance parameters permits to finish an effective model. |
| Publisher: |
Asian Network for Scientific Information, Pakistan (provided by DOAJ) |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 50 of 160 found articles
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