چکیده مقاله
Automatic language identification is a significant context of speech processing There have been numerous studies on automatic language identification context, in majority of which the extracted characteristic from speech signal ,PLP or MFCC were two factors In this study,a new language identification system is introduced in which characteristic exctraction will be based on Bessel Fourier transform factor and a new WRBF naurotic network as well as RBF Network are used in its category Results achieved from the new system were compared with results achieved through known methods of PLP&MFCC characteristic extraction as well as MLP neurotic network Results of assays performed on OGI database and pair by pair comparison of speeches depict a significant accuracy of language detection of RBF & WRBF network rather than MLP network Also,with respect to the fact that the accuracy of PLP&MFCC methods are so close to Fourier Bessel transform characteristic Extraction, this type of characteristic Extraction can be introduced as a powerful method in this context
کلیدواژهها
نویسندگان
Mostafa Modarresi
Electrical Electronic group, Engineering Department of Azad university Iran
Hadi Dehbovid
Electrical Electronic group, Engineering Department of Azad university Iran
شیوه ارجاع
Modarresi, Mostafa and Dehbovid, Hadi,1394,Automatic Language Identification using spectrum characteristics and Bessel funetions,International Conference on New Research Findings in Electrical Engineering and Computer Science,Tehran
ارائهشده در
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