S KOM 0608616 Bibliography

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DAFTAR PUSTAKA
Abdalla, M. I., & Ali, H. S. (2010, March). Wavelet-Based Mel-Frequency
Cepstral Coefficients for Speaker Identification using Hidden Markov
Models. JOURNAL OF TELECOMMUNICATIONS, 1(2), pp. 16-21.
Abdallah, S. J., Osman, I. M., & Mustafa, M. E. (2012). Text-Independent
Speaker Identification Using Hidden Markov Model. World of Computer
Science and Information Technology Journal (WCIST), 2(6), pp. 203-208.
Antoniou, A. (2006). Digital Signal Processing. New York: McGraw-Hill.
Buono, Agus., Mandasari. Yani., & Neyman, Shelvie Nidya. (2010)
Pengembangan Model Markov Tersembunyi untuk Pengenalan Kata
Berbahasa Indonesia. Seminar dan Call for Paper Munas Aptikom.
Bandung, Indonesia.
Fang, Chunsheng., 2009, From Dynamic Time Warping (DTW) to Hidden Markov
Model (HMM), Final project report for ECE742 Stochastic Decision,
University of Cincinnati, USA.
Gangisetty, Smitha. 2005. “Text-Independent Speaker Recognition”. College of
Engineering and Mineral Resources. Morgantown: West Virginia
University.
Holmes, J., & Holmes, W. (2001). Speech Synthesis and Recognition. London:

Taylor & Francis.

Rezdy Anugrah Perdana, 2014
Aplikasi Pengenalan Suara Pembicara Menggunakan Hidden Markov Model (HMM)
Universitas Pendidikan Indonesia | repository.upi.edu | perpustakaan.upi.edu

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Ihsan, Mahyus. 2006. “Pengembangan Model Markov Tersembunyi Pada
Identifikasi Pembicara”. Sekolah Pascasarjana. Bogor: Institut Pertanian
Bogor.
Ilyas, M. Z., Samad, S. A., Hussain, A., & Ishak, K. A. (2007). Speaker
Verification using Vector Quantization and Hidden Markov Model.
Student Conference on Research and Development, pp. 1 - 5.
Khairulvani, Feni. 2007. “Identifikasi Individu Melalui Suara Ucapan Dengan
Ekstraksi Ciri Mel-Frequency Cepstral Coefficient(MFCC) Sebagai Input
Jaringan Syaraf Tiruan”, Tugas Akhir, Institut Teknologi Bandung,
Bandung, Indonesia.
Manunggal, Heri Sugianto. 2010. “Perancangan dan pembuatan perangkat lunak
pengenalan suara pembicara dengan menggunakan analisa MFCC

feature extraction”. Program Studi Teknik Informatika. Surabaya:
Universitas Kristen Petra.
Muda, L., Begam, M., & Elamvazuthi, I. (2010, March 1). Voice Recognition
Algorithms using Mel Frequency Cepstral Coefficient (MFCC) and
Dynamic

Time

Warping

(DTW)

Techniques.

JOURNAL

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COMPUTING, vol 2(3), pp. 138-143.
Park, T. H. (2009). Introduction To Digital Signal Processing: Computer

Musically Speaking. Singapore: World Scientific Publishing Company.

Rezdy Anugrah Perdana, 2014
Aplikasi Pengenalan Suara Pembicara Menggunakan Hidden Markov Model (HMM)
Universitas Pendidikan Indonesia | repository.upi.edu | perpustakaan.upi.edu

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Pressman, R. S. (2005). Software engineering a practitioner's approach. New
York: McGraw- Hill.
Rabiner, L. R. (1989, February 1). A Tutorial on Hidden Markov Models
and Selected Applications in Speech Recognition. Proc. IEEE, 7(2), pp.
257-286.
Saha, G., Chakroborty. Sandipan., & Senapati, S. (2005) A New Silence Removal
and Endpoint Detection Algorithm for Speech and Speaker Recognition
Applications. Eleventh National Conference On Communications.
Kharagpur, India.
Santamarina, J. C. (2005). Discrete Signals And Inverse Problems An
Introduction For Engineers And Scientists. New Jersey: John Wiley &
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Suwandy. 2011. “Perancangan Program Aplikasi Absensi Pada Binus Learning
Community SAC Dengan Menggunakan Hidden Markov Model”.
Program Ganda Teknik Informatika dan Matematika. Jakarta: Universitas
Bina Nusantara.
Vaseghi, S. V. (2007). Multimedia Signal Processing. New Jersey: John Wiley &
Sons.

Rezdy Anugrah Perdana, 2014
Aplikasi Pengenalan Suara Pembicara Menggunakan Hidden Markov Model (HMM)
Universitas Pendidikan Indonesia | repository.upi.edu | perpustakaan.upi.edu