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Blind Deconvolution and Adaptive Algorithms for De-Reverberation

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Blind Deconvolution and Adaptive Algorithms for De-Reverberation Master Thesis Electrical Engineering with Emphasis on signal processing BLIND DECONVOLUTION AND ADAPTIVE ALGORITHMS FOR DE-REVERBERATION Suryavamsi Atresya Uppaluru Supervisor: Dr. Nedelko Grbic Examiner: Dr. Benny Sällberg Department of Signal Processing School of Engineering (ING) Blekinge Institute of Technology i This thesis is submitted to the School of Engineering at Blekinge Institute of Technology (BTH) in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering with emphasis on Signal Processing. Contact Information: Author: Suryavamsi Atresya Uppaluru E-mail: [email protected] Supervisor: Dr. Nedelko Grbic School of Engineering (ING) E-mail: [email protected] Phone: +46 455 38 57 27 Examiner: Dr. Benny Sällberg School of Engineering (ING) E-mail: [email protected] Phone: +46 455 38 55 87 School of Engineering Blekinge Institute of Technology Internet: www.bth.se/ing 371 79 Karlskrona Phone: +46 455 38 50 00 Sweden. Fax: +46 455 38 50 57 ii ACKNOWLEDGEMENT I would like to express sincere gratitude to our Supervisor Dr.Nedelko Gribic for his sagacious guidance and scholarly advice which enabled us to complete the thesis. I humbly thank the examiner Dr. Benny Sallberg for the encouragement and support. I express my deep gratitude to my parents in particular and my family who always reinforced every effort of mine. I would like to thank God and my friends for giving me constant support in every endeavor of mine. I would like to express my gratitude towards everyone who contributed their precious time and effort to help me, with whom I could complete my thesis successfully. Suryavamsi Atresya Uppaluru iii Master Thesis Electrical Engineering ABSTRACT Thesis no: MEEyy:xx Month Year Dereverberation of speech signals in a hands-free scenario by adaptive algorithms has been a research topic for several years now. However, it is still a challenging problem because of the nature of common room impulse response (RIR). RIR is generated artificially based on parameters of the room and its intensity depends on the size, shape, dimensions and materials used in the construction of the room. Speech signals recorded with a distant microphone in a usual room contains certain reverberant quality; this often causes severe degradation in automatic speech recognition performance. Resulting, the degradation of speech signal quality leads to reduced intelligibility to listeners. In this thesis Non Blind and Blind Deconvolution algorithms such as Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Recursive Least Square (RLS), Affine Projection Algorithm (APA) & Constant Modulus Algorithm (CMA) are implemented for removing reverberation in a room environment using a single microphone. The performances of these methods are analyzed using Reverberation Index (RR) and Speech Distortion (SD) parameters. The performances of these methods are tested for two different room sizes and three different reflection coefficients with a total of six different setups for five different filter orders. Keywords: Adaptive algorithms, CMA, Reverberation, Reverberation index, Speech Distortion. School of Computing Blekinge Institute of Technology 371 79 Karlskrona Sweden 1 Contents ABSTRACT ................................................................................................................................. 1 LIST OF FIGURES ...................................................................................................................... 3 LIST OF TABLES ........................................................................................................................ 4 LIST OF ABBREVIATIONS:....................................................................................................... 5 1 INTRODUCTION .................................................................................................................. 6 1.1 MOTIVATION FOR RESEARCH ............................................................................................ 6 1.2 RESEARCH QUESTION ....................................................................................................... 6 1.3 THESIS ORGANIZATION ..................................................................................................... 7 2 ROOM IMPULSE RESPONSE ............................................................................................. 8 2.1 REVERBERATION: ............................................................................................................. 8 2.2 REVERBERATION IN ENCLOSED PLACES ............................................................................ 10 2.3 IMAGE SOURCE MODEL: ................................................................................................. 12 2.3.1 Discrete time domain room impulse response ............................................................. 14 3 ADAPTIVE ALGORITHMS ............................................................................................... 18 3.1 ADAPTIVE CHANNEL EQUALIZATION ............................................................................... 18 3.2 LEAST MEAN SQUARE (LMS) ALGORITHM: ..................................................................... 18 3.3 NORMALIZED LMS ALGORITHM: .................................................................................... 19 3.4 RLS ALGORITHM:........................................................................................................... 21 3.5 AFFINE PROJECTION ALGORITHM: ................................................................................... 22 4 BLIND DECONVOLUTION ............................................................................................. 24 4.1 REVERBERATION CANCELLATION .................................................................................... 24 4.2 BLIND DECONVOLUTION: ................................................................................................ 25 4.3 CONSTANT MODULUS ALGORITHM (CMA): .................................................................... 25 4.3.1 Properties of Constant Modulus: ................................................................................ 28 4.3.2 Advantages of CMA: .................................................................................................. 28 4.3.3 Disadvantages of CMA: ............................................................................................. 28 5 DESIGN AND IMPLEMENTATION ................................................................................. 29 5.1 MICROPHONE SETUP ....................................................................................................... 29 5.2 THIRAN FRACTIONAL DELAY FILTER: .............................................................................. 30 5.3 ROOM IMPULSE RESPONSE: ............................................................................................. 30 5.4 LMS: ............................................................................................................................. 33 5.5 NLMS: .......................................................................................................................... 33 5.6 RLS: .............................................................................................................................. 34 5.7 APA: ............................................................................................................................. 34 5.8 CMA: ............................................................................................................................ 35 5.9 MEASUREMENT OF REVERBERATION SUPPRESSION (DE-REVERBERATION) ....................... 35 5.9.1 Reverberation Index (RR): ......................................................................................... 35 5.9.2 Speech Distortion (SD): ............................................................................................. 36 6 RESULTS ............................................................................................................................. 37 6.1 TEST SIGNAL: ................................................................................................................. 37 6.2 EVALUATION OF LMS, RLS, NLMS, APA AND CMA METHODS USING 6 DIFFERENT SETUPS 38 6.2.1 Setup-1 ...................................................................................................................... 38 6.2.2 Setup-2 ...................................................................................................................... 39 6.2.3 Setup-3 ...................................................................................................................... 40 6.2.4 Setup-4 ...................................................................................................................... 41 6.2.5 Setup-5 ...................................................................................................................... 42 6.2.6 Setup-6 ...................................................................................................................... 43 7 CONCLUSION AND FUTURE WORK.............................................................................. 45 8 REFERENCES ..................................................................................................................... 46 2 LIST OF FIGURES Figure 2.1: Illustration of a desired source, a microphone, and interfering sources. ............... 8 Figure 2.1.1: Application of acoustic signal processing concerned
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