Reporter ： Chia-Cheng Chen Advisor ： Wen-Ping Chen

1. A Study of Single Channel Blind Source Separation and Recognition Based on Mixed-State Prediction Reporter：Chia-Cheng Chen Advisor ：Wen-Ping Chen Department of Electrical Engineering National Kaohsiung University of Applied Sciences Network Application Laboratory

2. Outline • Introduction and Motivation • Background • Research Methods • Experimental Results • Conclusion and Future Works • Research Results

3. Introduction • The applications of voiceprintrecognition system • Call routing (1997) • Jupiter (1997) • Let’s Go! (2002) • Siri(2010) • Skyvi (2011) • Vlingo (2011)

4. Introduction • Current Ecological Status of the Survey: • Sensor networks • Wireless networks • Database • Voiceprint recognition system • Advantage • Reduce the cost of human resource and time • Save and share the raw data conveniently

5. Introduction Blind Source Separation http://metadata.froghome.org/about.php台灣地區兩棲類物種描述資料

6. Introduction ? Blind Source Separation

7. Introduction • Voiceprint recognition • C.J. Huang, Y.J. Yang, D.X. Yang and Y.J. Chen, “Frog classification using machine learning techniques,” Expert Systems with Applications, Vol. 36, No. 2, pp. 3737-3743, 2009. (SCI) • S.C. Hsieh, W.P. Chen, W.C. Lin, F.S. Chou, and J.R. Lai, “Endpoint detection of frog croak syllableswith using average energy entropy method,” Taiwan Journal of Forest Science, Vol.27, No.2, pp.149-161, Jun. 2012. (EI) • W.P. Chen, S.S. Chen, C.C. Lin, Y.Z. Chen and W.C. Lin, “Automatic recognition of frog call using multi-stage average spectrum,” Computers & Mathematics with Applications, Vol. 64, No. 5, pp. 1270-1281, Sep. 2012. (SCI)

8. Introduction • Single channel source separation • M.N. Schmidt and M. Mørup, “Nonnegative matrix factor 2-D deconvolution for blind single channel source separation,” Proceedings of International Conferences Independent Component Analysis and Blind Signal Separation, Vol. 3889, pp. 700-707, Mar. 2006. (SCI) • S. Kırbız and B. Gunsel, “Perceptually weighted non-negative matrix factorization for blind single-channel music source separation,” 21st International Conference on Pattern Recognition, Nov. 2012. (EI)

9. Motivation • Automatic frog species voiceprint recognition system • Predicting the number of mixed signal • Single channel blind source separation • Biologist • People

10. Outline • Introduction and Motivation • Background • Research Methods • Experimental Results • Conclusion and Future Works • Research Results

11. Background

12. Background • Voiceprint Recognition

13. SignalProcessing • Signal Processing Resample 44100Hz Frog Signal Pre-emphasis Frame Hamming Window

14. Syllable Segmentation • Endpoint Detection Algorithm • Energy • Time Domain • Simple • Square of the Amplitude or Absolute Value of the Amplitude • Vulnerable to Noise Impact • Entropy • Frequency Domain • Complex • Noise Immunity

15. Average Energy Entropy • Signal Transform • Average Energy s(n)：windowed signal N：frame size k：frequency component u：the mean for energy of input signal A(n)：the amplitude value of input signal N：total number of input signal

16. Average Energy Entropy • Probability Density Function E(fi)：the spectral energy for the frequency fi ：the corresponding probability density M：total number of frequency components in FFT β： Multiples

17. Average Energy Entropy • Average Energy Entropy H’：the negative entropy for each frame

18. Endpoint Detection Algorithm Signal AEE Absolute Energy Square Energy

19. Feature Extraction

20. Adaptive Multi-stage Average Spectral • Adaptive Clustering Cluster B Cluster A

21. Adaptive Multi-stage Average Spectral • Adaptive Clustering Cluster B Cluster A

22. Adaptive Multi-stage Average Spectral • Adaptive Clustering

23. Adaptive Multi-stage Average Spectral • Template Training Frame 1 Stage 1 Frame 2 Frame 3 Stage 2 Frame 4 Frame 5 Frame 6 Stage 3 Frame 7

24. Adaptive Multi-stage Average Spectral • Template Training

25. Adaptive Multi-stage Average Spectral • Template Training Minimum  Cumulative  Difference

26. Adaptive Multi-stage Average Spectral • Template Maching Minimum  Cumulative  Difference

27. Blind Source Separation ， • Non-negative Matrix Factor 2-D Deconvolution • αbasis matrix and βcoefficient matrix • Obtain the relations between the time and the pitch • Shift operator ， V: Original Signal : Reconstructed Signal

28. Non-negative Matrix Factor 2-D Deconvolution

29. Non-negative Matrix Factor 2-D Deconvolution • Non-negative Matrix Factor 2-D Deconvolution • Cost function • Based on Euclidean Distance • Based on Kullback-Leibler Divergence

30. Outline • Introduction and Motivation • Background • Research Methods • Experimental Results • Conclusion and Future Works • Research Results

31. Research Methods • Mixed-State Prediction voiceprint recognition method • Training • Mixed signals states • Testing • Two stages voiceprint recognition • Mixed-State Prediction

33. First Stage Independent signal Mixed signal Latouche'sfrog MFCC Moltrecht's green tree frog + Latouche'sfrog MFCC

34. Mixed signals states

35. Mixed States • Average Energy Independent signal Mixed signal E：the average energy for the frequency X(k) N：the length of the syllable

36. Predicting the number of mixed signal E：the mean spectral energy for test syllable a：the mean energy of training data T：the separation threshold

37. Outline • Introduction and Motivation • Background • Research Methods • Experimental Results • Conclusion and Future Works • Research Results

38. Experimental Results

39. Experimental Results • Recognition Experiment • Independent signals

40. Experimental Results • Recognition Experiment • Mixed signals

41. Experimental Results

42. Experimental Results

43. Conclusion and Future Works • The proposed method • Improve the mixed signal recognition rate • Proposed a method to predict the number of mixed signal

44. Conclusion and Future Works • Future Works • Study of de-noise methods • Collect more features between independent and mixed signals • Mixed signals recognition within same species • Collect various sound of species. Then, improve the system performance • Adopt Support Vector Machines(SVM), Neural Network…

45. Research Results • Competition • 第七屆數位訊號處理創思設計競賽—入圍 • 青蛙物種聲紋辨識系統 • 計畫協助

46. Thank you for your attention !!