Klasifikasi Gender Berdasarkan Suara Menggunakan Support Vector Machine

Authors

  • Raditya Budi Handoko Telkom University
  • Suyanto Suyanto

DOI:

https://doi.org/10.21108/INDOJC.2019.4.1.244

Abstract

Klasifikasi gender berdasarkan suara mempengaruhi tingkat performansi dari identifikasi suara. oleh karena itu penelitian tugas akhir ini penulis membuat sistem klasifikasi gender berdasarkan suara. penelitian ini menggunakan dataset berupa rekaman suara sebanyak 2260 suara yang terbagi menjadi dua kelas yaitu "laki-laki" dan "perempuan". Untuk proses ekstrasi ciri digunakan Mel-Frequency Cepstral (MFCC) untuk menghasilkan vektor ciri dari sinyal suara. dalam proses klasifikasi digunakan metode Support Vector Machine (SVM). Hasil akurasi SVM tertinggi untuk klasifikasi gender berdasarkan suara dapat mencapai 100\% menggunakan kernel Polynomial dengan degree = 1.

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References

Jamil Ahmad, Mustansar Fiaz, Soon-il Kwon, Maleerat Sodanil, Bay Vo, and Sung Wook Baik. Gender identification using mfcc for telephone applications-a comparative study. arXiv preprint arXiv:1601.01577, 2016.

Sreedhar Bhukya. Effect of gender on improving speech recognition system. International Journal of Computer Applications, 179:22–30, 2018.

Kashyap Patel and RK Prasad. Speech recognition and verification using mfcc & vq. Int. J. Emerg. Sci. Eng.(IJESE), 1(7), 2013.

Urmila Shrawankar and Vilas M Thakare. Techniques for feature extraction in speech recognition system: A comparative

study. arXiv preprint arXiv:1305.1145, 2013

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Published

2019-03-22

How to Cite

Handoko, R. B., & Suyanto, S. (2019). Klasifikasi Gender Berdasarkan Suara Menggunakan Support Vector Machine. Indonesian Journal on Computing (Indo-JC), 4(1), 9–18. https://doi.org/10.21108/INDOJC.2019.4.1.244

Issue

Vol. 4 No. 1 (2019): Maret, 2019

Section

Computer Science

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