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Mel-frequencies Stochastic Model for Gender Classification based on Pitch and Formant

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@article{IJASEIT615,
   author = {Syifaun Nafisah and Oyas Wahyunggoro and Lukito Edi Nugroho},
   title = {Mel-frequencies Stochastic Model for Gender Classification based on Pitch and Formant},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {6},
   number = {2},
   year = {2016},
   pages = {124--129},
   keywords = {Speech Recognition; Gender Identity; Mel-frequencies, Stochastic Model; Noisy Environment; Formants, Pitch},
   abstract = {

Speech recognition applications are becoming more and more useful nowadays. Before this technology is applied, the first step is test the system to measure the reliability of system.  The reliability of system can be measured using accuracy to recognize the speaker such as speaker identity or gender.  This paper introduces the stochastic model based on mel-frequencies to identify the gender of speaker in a noisy environment.  The Euclidean minimum distance and back propagation neural networks were used to create a model to recognize the gender from his/her speech signal based on formant and pitch of Mel-frequencies. The system uses threshold technique as identification tool. By using this threshold value, the proposed method can identifies the gender of speaker up to 94.11% and the average of processing duration is 15.47 msec. The implementation result shows a good performance of the proposed technique in gender classification based on speech signal in a noisy environment.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=615},    doi = {10.18517/ijaseit.6.2.615} }

EndNote

%A Nafisah, Syifaun
%A Wahyunggoro, Oyas
%A Nugroho, Lukito Edi
%D 2016
%T Mel-frequencies Stochastic Model for Gender Classification based on Pitch and Formant
%B 2016
%9 Speech Recognition; Gender Identity; Mel-frequencies, Stochastic Model; Noisy Environment; Formants, Pitch
%! Mel-frequencies Stochastic Model for Gender Classification based on Pitch and Formant
%K Speech Recognition; Gender Identity; Mel-frequencies, Stochastic Model; Noisy Environment; Formants, Pitch
%X 

Speech recognition applications are becoming more and more useful nowadays. Before this technology is applied, the first step is test the system to measure the reliability of system.  The reliability of system can be measured using accuracy to recognize the speaker such as speaker identity or gender.  This paper introduces the stochastic model based on mel-frequencies to identify the gender of speaker in a noisy environment.  The Euclidean minimum distance and back propagation neural networks were used to create a model to recognize the gender from his/her speech signal based on formant and pitch of Mel-frequencies. The system uses threshold technique as identification tool. By using this threshold value, the proposed method can identifies the gender of speaker up to 94.11% and the average of processing duration is 15.47 msec. The implementation result shows a good performance of the proposed technique in gender classification based on speech signal in a noisy environment.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=615 %R doi:10.18517/ijaseit.6.2.615 %J International Journal on Advanced Science, Engineering and Information Technology %V 6 %N 2 %@ 2088-5334

IEEE

Syifaun Nafisah,Oyas Wahyunggoro and Lukito Edi Nugroho,"Mel-frequencies Stochastic Model for Gender Classification based on Pitch and Formant," International Journal on Advanced Science, Engineering and Information Technology, vol. 6, no. 2, pp. 124-129, 2016. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.6.2.615.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Nafisah, Syifaun
AU  - Wahyunggoro, Oyas
AU  - Nugroho, Lukito Edi
PY  - 2016
TI  - Mel-frequencies Stochastic Model for Gender Classification based on Pitch and Formant
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 6 (2016) No. 2
Y2  - 2016
SP  - 124
EP  - 129
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - Speech Recognition; Gender Identity; Mel-frequencies, Stochastic Model; Noisy Environment; Formants, Pitch
N2  - 

Speech recognition applications are becoming more and more useful nowadays. Before this technology is applied, the first step is test the system to measure the reliability of system.  The reliability of system can be measured using accuracy to recognize the speaker such as speaker identity or gender.  This paper introduces the stochastic model based on mel-frequencies to identify the gender of speaker in a noisy environment.  The Euclidean minimum distance and back propagation neural networks were used to create a model to recognize the gender from his/her speech signal based on formant and pitch of Mel-frequencies. The system uses threshold technique as identification tool. By using this threshold value, the proposed method can identifies the gender of speaker up to 94.11% and the average of processing duration is 15.47 msec. The implementation result shows a good performance of the proposed technique in gender classification based on speech signal in a noisy environment.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=615 DO - 10.18517/ijaseit.6.2.615

RefWorks

RT Journal Article
ID 615
A1 Nafisah, Syifaun
A1 Wahyunggoro, Oyas
A1 Nugroho, Lukito Edi
T1 Mel-frequencies Stochastic Model for Gender Classification based on Pitch and Formant
JF International Journal on Advanced Science, Engineering and Information Technology
VO 6
IS 2
YR 2016
SP 124
OP 129
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 Speech Recognition; Gender Identity; Mel-frequencies, Stochastic Model; Noisy Environment; Formants, Pitch
AB 

Speech recognition applications are becoming more and more useful nowadays. Before this technology is applied, the first step is test the system to measure the reliability of system.  The reliability of system can be measured using accuracy to recognize the speaker such as speaker identity or gender.  This paper introduces the stochastic model based on mel-frequencies to identify the gender of speaker in a noisy environment.  The Euclidean minimum distance and back propagation neural networks were used to create a model to recognize the gender from his/her speech signal based on formant and pitch of Mel-frequencies. The system uses threshold technique as identification tool. By using this threshold value, the proposed method can identifies the gender of speaker up to 94.11% and the average of processing duration is 15.47 msec. The implementation result shows a good performance of the proposed technique in gender classification based on speech signal in a noisy environment.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=615 DO - 10.18517/ijaseit.6.2.615