Rabiner L, Juang BH Fundamental of Speech Recognition. New Jersey: PTR Prentice-Hall, Inc. Reynolds D.A An Overview of Automatic

Transkripsi

1 DAFTAR PUSTAKA Bolat B, Yildirim T Performance increasing methods for probabilistic Neural Networks. Pakistan Journal of Information and Technology 2(3): Campbell, J.P., 1997, Speaker Recognition: A Tutorial, Proceedings of the IEEE, Vol. 85, No. 9. Furui S Recent advances in speaker recognition. Pattern Recognition Letters 18: Ganchev T, Tsopanoglou A, Fakotakis N, Kokkinakis G. 2002a. Probabilistic Neural Networks Combined with GMMs for Speaker Recognition over Telephone Channels. 14th Int. Conf. On Digital Signal Processing, 2: Ganchev T, Fakotakis N, Kokkinakis G. 2002b. Speaker Verification System Based On Probabilistic Neural Neworks. NIST Speaker Recognition Evaluation Workshop, Virginia, USA. Ganchev T Speaker Recognition. Department of Computer and Electrical Engineering, University of Patras, Greece. [disertasi] [7 Mei 2007] Johnson R. A, Wichern R.E Applied Multivariate Statistical Analysis. New Jersey, USA: Printice Hall, Inc. Kantardzic, M Data Mining: Concepts, Models, Methods, and Algorithms. New Jersey, USA: John Wiley & Sons, Inc. Karpov E Real-Time Speaker Identification [tesis]. Joensuu: department of Computer Science, Unversity of Joensuu. Kusumadewi S Artificial Intelligence (Teknik dan Aplikasinya). Yogyakarta: Graha Ilmu. Li Min Fu Neural Networks in Computer Intelligence. New York: The McGraw-Hill, Inc. Low R, Togneri R Speech Recognition Using the Probabilistic Neural Network. tr98-01.pdf [19 September 2005] Porat B A Course in Digital Signal Processing. New York: John Wiley & Sons, Inc. Pressman, R.S Software Engineering : A Practitioner s Approach. New York: The McGraw-Hill, Inc. Rabah Y. 2004, VoiceXML Speech Recognition. [19 September 2005]

2 53 Rabiner L, Juang BH Fundamental of Speech Recognition. New Jersey: PTR Prentice-Hall, Inc. Reynolds D.A An Overview of Automatic Speaker Recognition Technology. ICASSP: Russel SJ. Norvig P Artificial Intelligence A Modern Approach. New Jersey: Prentice-Hall, Inc. Shiavi R Introduction to Applied Statistical Signal Analysis. USA: R.D. Irwin, Inc. Specht D F Probabilistic Neural Networks and Polynomial Adaline as Complementary Techniques for Classification. IEEE Transaction on Neural Networks 1(1): Enhancements to Probabilistic Neural Networks. IEEE Transaction on Neural Networks 3(1): Specht D F, Shapiro P D Generalization Accuracy of Probabilistic Neural Networks Compared with Back-Propagation Networks. IEEE Transaction on Neural Networks 1: The Mathworks, Inc., 2004, Signal Processing Blockset, User s Guide, Versi 6, [19 September 2005] Zaknich A A Modified Probabilistic Neural Networks for Signal Processing and Pattern Recognition [disertasi]. Western Australia: Department of Electrical and Electronic Engineering, The University of Western Australia.

3 54 Lampiran 1 Bentuk sinyal suara Anta (asli) Anta (noise 20 desibel) Anta (noise 30 desibel)

4 55 Lanjutan Aziz (asli) Aziz (noise 20 desibel) Aziz (noise 30 desibel)

5 56 Lanjutan Citra (asli) Citra (noise 20 desibel) Citra (noise 30 desibel)

6 57 Lanjutan Didit (asli) Didit (noise 20 desibel) Didit (noise 30 desibel)

7 58 Lanjutan Fitri (asli) Fitri (noise 20 desibel) Fitri (noise 30 desibel)

8 59 Lanjutan Intan (asli) Intan (noise 20 desibel) Intan (noise 30 desibel)

9 60 Lanjutan Mijo (asli) Mijo (noise 20 desibel) Mijo (noise 30 desibel)

10 61 Lanjutan Sumrah (asli) Sumrah (noise 20 desibel) Sumrah (noise 30 desibel)

11 62 Lanjutan Titin (asli) Titin (noise 20 desibel) Titin (noise 30 desibel)

12 63 Lanjutan Wiwie (asli) Wiwie (noise 20 desibel) Wiwie (noise 30 desibel)

13 Lampiran 2 Visualisasi grafis hasil pengujian data asli 64

14 Lanjutan 65

15 Lanjutan 66

16 Lanjutan 67

17 Lampiran 3 Visualisasi grafis hasil pengujian data noise 68

18 Lanjutan 69

19 Lanjutan 70

20 Lanjutan 71

21 Lanjutan 72

22 Lanjutan 73

23 Lampiran 4 Perbandingan hasil pengujian data asli dan data noise 74

24 Lanjutan 75