Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods

Cigdem Bakir [1]


In our age, technological developments are accompanied by certain problems associated with them. Security takes the first place amongst such kind of problems. In particular, such biometric systems as authentication constitute the significant fraction of the security matters. This is because sound recordings having connection with the various crimes are required to be analyzed for forensic purposes. Authentication systems necessitate transmission, design and classification of biometric data in a secure manner. In this study, analysis of German language employed in the economy, industry and trade in a wide spread manner, has been performed. In the same vein, the aim was to actualize automatic voice and speech recognition system using Mel Frequency Cepstral Coefficients (MFCC), MelFrequency Discrete Wavelet Coefficients (MFDWC) and Linear. Prediction Cepstral Coefficient (LPCC) taking German sound forms and properties into consideration. Approximately 2658 German voice samples of words and clauses with differing lengths have been collected from 50 males and 50 females. Features of these voice samples have been obtained using wavelet transform. Feature vectors of the voice samples obtained have been trained with such methods as Boltzmann Machines and Deep Belief Networks. In the test phase, owner of a given voice sample has been identified taking the trained voice samples into consideration. Results and performances of the algorithms employed in the study for classification have been also demonstrated in a comparative manner.

Boltzmann Machines
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Subjects Engineering
Journal Section Research Article
Authors

Author: Cigdem Bakir
Institution: YILDIZ TEKNIK UNIV
Country: Turkey


Dates

Publication Date : December 1, 2016

Bibtex @research article { ijamec280579, journal = {International Journal of Applied Mathematics Electronics and Computers}, issn = {}, eissn = {2147-8228}, address = {}, publisher = {Selcuk University}, year = {2016}, volume = {}, pages = {399 - 403}, doi = {10.18100/ijamec.280579}, title = {Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods}, key = {cite}, author = {Bakir, Cigdem} }
APA Bakir, C . (2016). Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods. International Journal of Applied Mathematics Electronics and Computers , (Special Issue-1) , 399-403 . DOI: 10.18100/ijamec.280579
MLA Bakir, C . "Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods". International Journal of Applied Mathematics Electronics and Computers (2016 ): 399-403 <https://dergipark.org.tr/en/pub/ijamec/issue/25619/280579>
Chicago Bakir, C . "Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods". International Journal of Applied Mathematics Electronics and Computers (2016 ): 399-403
RIS TY - JOUR T1 - Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods AU - Cigdem Bakir Y1 - 2016 PY - 2016 N1 - doi: 10.18100/ijamec.280579 DO - 10.18100/ijamec.280579 T2 - International Journal of Applied Mathematics Electronics and Computers JF - Journal JO - JOR SP - 399 EP - 403 VL - IS - Special Issue-1 SN - -2147-8228 M3 - doi: 10.18100/ijamec.280579 UR - https://doi.org/10.18100/ijamec.280579 Y2 - 2016 ER -
EndNote %0 International Journal of Applied Mathematics Electronics and Computers Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods %A Cigdem Bakir %T Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods %D 2016 %J International Journal of Applied Mathematics Electronics and Computers %P -2147-8228 %V %N Special Issue-1 %R doi: 10.18100/ijamec.280579 %U 10.18100/ijamec.280579
ISNAD Bakir, Cigdem . "Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods". International Journal of Applied Mathematics Electronics and Computers / Special Issue-1 (December 2016): 399-403 . https://doi.org/10.18100/ijamec.280579
AMA Bakir C . Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods. International Journal of Applied Mathematics Electronics and Computers. 2016; (Special Issue-1): 399-403.
Vancouver Bakir C . Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods. International Journal of Applied Mathematics Electronics and Computers. 2016; (Special Issue-1): 403-399.