1. 1 ( قالوا سبحانك لا علم لنا الإ ما علمتنا إنك أنت العليم الحكيم ) صدق الله العظيم سورة البقرة آيه 32

2. 2 Speech Compression Using Wavelet Packets Tree Nodes LPC Encoding and Best Tree Encoding (BTE) Features Presented by: Eng. Mohammed Yahia Mohammed Presented by: Eng. Mohammed Yahia Mohammed

3. 3 Dr: Amr R. Gody Electrical Engineering Department Faculty of Engineering, Fayoum University Dr: Amr R. Gody Electrical Engineering Department Faculty of Engineering, Fayoum University Dr: Tamer M. Barakat Electrical Engineering Department Faculty of Engineering, Fayoum University Dr: Tamer M. Barakat Electrical Engineering Department Faculty of Engineering, Fayoum University Dr: Safy Ahmed Department of Engineering, Nuclear Research Center, Atomic Energy Authority, Egypt Dr: Safy Ahmed Department of Engineering, Nuclear Research Center, Atomic Energy Authority, Egypt

4. 4 OUTLINE Problem Description Wavelet Packet Decomposition Best Tree Encoding (BTE) Proposed System Experiments and Results Conclusion Future Work 4

5. 5 OUTLINE Problem Description 5

6. 6 Speech compression is one of the major areas in speech processing. speech compression makes it possible for more users to share the available system. Speech compression is a process of converting human speech into efficient encoded representations that can be decoded to produce a close approximation of the original signal. speech compression is needed in digital voice storage. compression makes it possible to store longer messages Problem Description

7. 7 OUTLINE Problem Description Wavelet Packet Decomposition 7

8. 8 Wavelet function is finite in time. It is also finite in frequency

9. 9 OUTLINE Problem Description Wavelet Packet Decomposition Best Tree Encoding (BTE) 9

10. 10 Best Tree Encoding (BTE)

11. 11 Best Tree Encoding (BTE)

12. 12 Best Tree Encoding (BTE)

13. 13 Best Tree Encoding (BTE)  Apply the encoding by considering clusters of 7 bands.  Each cluster will be encoded in 7 bits such that each bit is associated to a certain band.

14. 14 Best Tree Encoding (BTE) Apply the best tree algorithm to optimize the full binary tree. The optimization minimizes the number of tree nodes such that it best fit the information included in the speech signal. ElementBinary ValueDecimal valueFrequency Band V10001100120 - 25 % V210000006425% - 50% V30000000050%-75% V40000100475%- 100%

15. 15 Best Tree Encoding (BTE) Elemen t Binary Value Decimal value Frequency Band V10100011350 - 25 % V21000006425% - 50% V300110112750%-75% V41000006475%- 100% Real Example For one Frame 35642764 BTE Code

16. 16 OUTLINE Problem Description Wavelet Packet Decomposition Best Tree Encoding (BTE) Proposed System 16

17. 17 Proposed System Encoder process

18. 18 Proposed System Encoder process BTE WPDEC Best Tree LPC for each Leaf Speech Time waveform

19. 19 Proposed System BTE Decoder LPC Inverse Filters WPREC Speech Time waveform De-coder process

20. 20 OUTLINE Problem Description Wavelet Packet Decomposition Best Tree Encoding (BTE) Proposed System Experiments and Results 20

21. 21 Experiments and Results  Three real speeches (male spoken, female spoken, music) have been used. DaubechiesDaubechies4  Using Daubechies wavelet family and using level 4 to decompose the speech signal.Daubechies  The encoding algorithm is compared with the original speech files using SNR, MSE and SD.  These experimental results were done on a PC with an Intel CORE i7 processor and 4 Mb RAM.

22. 22 Experiments and Results Signal to Noise Ratio : Mean Square Error : Spectral distortion : Compression Ratio (CR) :

23. 23 Experiments and Results Wavelet Family CRSNRMSESD Haar4.3592-3.43620.061914.7434 db25.0010-2.37410.048514.3272 db35.1681-1.43420.039015.9855 db45.5047-1.44700.039116.3801 Output CR, SNR, MSE and SD for all wavelet filter for male speech

24. 24 Experiments and Results Wavelet Family CRSNRMSESD Haar3.9075-8.92480.054419.4787 db25.1435-6.97360.034717.9986 db35.2521-5.49170.024716.1132 db45.4534-5.36820.024015.8379 Output CR, SNR, MSE and SD for all wavelet filter for female speech

25. 25 Experiments and Results Wavelet Family CRSNRMSESD Haar5.8606-7.36260.083116.9042 db27.1404-5.66870.056316.2140 db39.7198-4.11190.039315.3065 db49.7601-3.68470.035615.1088 Output CR, SNR, MSE and SD for all wavelet filter for music speech

26. 26 Experiments and Results Output Waveform of male spoken with db4

27. 27 Experiments and Results Output Waveform of female spoken with db4

28. 28 Experiments and Results Output Waveform of music with db4

29. 29 OUTLINE Problem Description Wavelet Packet Decomposition Best Tree Encoding (BTE) Proposed System Experiments and Results Conclusion 29

30. 30 Conclusion  The problem of having dynamic size feature vectors is solved by considering the 4 points encoding algorithm.  The negative value of SNR in the obtained results is due to some factors that will be considered in future work.  The main objective of this research is to explore the validity of BTE in such compression application.  Speech understanding was our target but not the quality of the produced speech.

31. 31 OUTLINE Problem Description Wavelet Packet Decomposition Best Tree Encoding (BTE) Proposed System Experiments and Results Conclusion Future Work 31

32. 32 Future Work  Considering of the proper filter excitation source in the inverse LPC filter.  Speech quality will be our target.

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