Ppt on voice recognition system using matlab

Using Mobile Phones To Write In Air Chris Coykendall – ODU CS495.

Voice recording technologies are cumbersome to search through (and speech-to-text software can be hit or miss) Primary Goals To explore the viability of using mobile phone accelerometers to write in the air. To understand and overcome limitations with character recognition. To develop a prototype on the Nokia N95 platform and perform a test study. Challenges Lack of a gyroscope Many systems/server-side implementation was developed in MATLAB, which they were able to use basic libraries for the signal /


Voices of the Partner Disciplines: Mathematical Needs of Other Departments.

volume: A Collective Vision: Voices of the Partner Disciplines, edited/stress problem solving, with the incumbent recognition of ambiguities. Courses should stress conceptual/use of models.” “Models are a way of organizing information for the purpose of gaining insight and providing intuition into systems/ that are too complex to understand any other way”. “Students should master a higher level interface, e.g.: spreadsheet, symbolic/numerical computational packages( e.g. Mathematica, Maple, Matlab/


UNIT - I Data Mining. UNIT - I Introduction : Fundamentals of data mining, Data Mining Functionalities, Classification of Data Mining systems, Major issues.

Many more… Origins of Data Mining Draw ideas from machine learning / AI, Pattern recognition and databases. Traditional techniques may be unsuitable due to  Enormity of data  /, audio, and video data. They are used in applications such as picture content-based retrieval, voice-mail systems, video-on-demand systems, the World Wide Web, and speech-based/Daubechie4 Implementing 2D-DWT 134 Decomposition ROW i COLUMN j 2-D DWT ON MATLAB Load Image (must be.mat file) Choose wavelet type Hit Analyze Choose display/


Probability & Random Variables Jungwon University Prof. Jae Young Choi, Ph.D. Medical Imaging & Pattern Recognition Lab. Department of Biomedical Engineering.

Recognition Lab. Department of Biomedical Engineering Email: jyoung.choi@jwu.ac.kr URL: http://bprlab.tistory.com/notice/4 Probability & Random Variables PROBABILITY ◈ OBJECTIVES – 확률, 불규칙 변수와 신호의 이론과 응용에 대해 공부 –D/ Random Signal: 어떤 확률적인 방식에 의해서만 그 특성이 결정되는 시간의 함수인 파 형 및 신호 –Ex) Broadcasting Radio Receiver Voice = Desirable Waveform (Information) + Undesirable Waveform (Noise) = v(t) + n(t) –Ex) Television System/ 4 인에게 분배하는 Program [Use Uniform Distribution in Your PC, rand() in Matlab or random() in C/C++]


Probability & Random Variables Jungwon University Prof. Jae Young Choi, Ph.D. Medical Imaging & Pattern Recognition Lab. Department of Biomedical Engineering.

Recognition Lab. Department of Biomedical Engineering Email: jyoung.choi@jwu.ac.kr URL: http://bprlab.tistory.com/notice/4 Probability & Random Variables PROBABILITY ◈ OBJECTIVES – 확률, 불규칙 변수와 신호의 이론과 응용에 대해 공부 –D/ Random Signal: 어떤 확률적인 방식에 의해서만 그 특성이 결정되는 시간의 함수인 파 형 및 신호 –Ex) Broadcasting Radio Receiver Voice = Desirable Waveform (Information) + Undesirable Waveform (Noise) = v(t) + n(t) –Ex) Television System/ 4 인에게 분배하는 Program [Use Uniform Distribution in Your PC, rand() in Matlab or random() in C/C++]


Qualcomm. Background A leading designer and manufacturer of chipsets and system software used in cutting-edge wireless applications, handsets, and related.

that allow both wireless and wired systems to communicate with other devices of the same ability M2M uses a device to capture an event,/the technologies of improving the performance of 3G voice services to achieve the goal of clear voice message delivery.The research involves noise cancellation,/recognition, image analysis and synthesis research Multimedia Applications Development Laboratory (MADLab) 3D Motion Capture Laboratory Recording human movement in 3D. Equipped with an optical motion capture system/


PhonePoint Pen: Using Mobile Phones to Write in Air Sandip Agrawal, Ionut Constandache, Shravan Gaonkar, Romit Roy Choudhury ACM MobiHeld 2009.

 Time consuming to browse through voice messages So, need a solution that is  Easy to use  Always-with-me  Allows /MATLAB several design challenges emerge … Design Challenges (1)  Hands rotate while writing  Accelerometers only measure linear acceleration  Rotation injects ambiguity (Wii uses/ Of Course, Not a Product Yet  Lowercase character recognition  Cursive handwriting more complicated  Need smaller hand movements/ … The vision is: Thanks Visit Systems Networking Research Group (SyNRG) @ Duke/


Institute for Software Integrated Systems Vanderbilt University CYBER PHYSICAL SYSTEMS (CPS) Janos Sztipanovits ISIS, Vanderbilt University.

done) – involve major effort due to overly complex modeling languages, – use a wide range of formalisms and Impact is far-reaching – tool chains / semantics Modeling Controller Synthesis System Analysis Code Synthesis Validation Verification Target Analysis Platform Simulink Stateflow ECSL/GME Ptolemy Matlab Simulator Checkmate SAL Teja /Hoc Network Data Images Voice Video Mission Planning & Prep Situation Understanding Battle Mgmt & Execution Sensor Fusion Target Recognition Integrated Sustainment Embedded /


CS162 Operating Systems and Systems Programming Lecture 25 Why Systems Fail and What We Can Do About It November 30, 2011 Anthony D. Joseph and Ion Stoica.

against fire, flood, sabotage,.. –Redundant system and service at remote site. –Use design diversity Lec 25.5 11/30/2011 Anthony D. Joseph and Ion/down. Because Siri depends on servers to do the heavy computing required for voice recognition, the service is useless without that connection. Network outages caused the disruption according/data –Iterative algorithms (e.g. machine learning, graphs) –Interactive data mining (e.g. Matlab, Python, SQL) Lec 25.33 11/30/2011 Anthony D. Joseph and Ion Stoica /


Pre-processing Idea: Post-processing Network Pre-processing

selection decide which features to use e.g. Character recognition b e.g. Character recognition For a 256 x 256/ advance due to constraints on processing power Another technique (used in eg Matlab) is to look at the contribution to the overall variance/ selectively tune to and follow one of a number of (independent) voices despite noise, delays, water in your ear lecturer droning on etc etc/signals, the transformation of the observation vector x by a neural system into a new vector y should be carried out in a/


Characteristics of Big Data Applications and Scalable Software Systems Chesapeake Large-Scale Analytics Conference Loews Annapolis Hotel Annapolis October.

Extensions (Spark, Twister)MPI, Giraph Integrated Systems such as Hadoop + Harp with Compute and Communication model separated Correspond to First 4 Big Data Architectures Useful Set of Analytics Architectures Pleasingly Parallel: including /Geometric TodoPP 3D feature extractionTodoPP Deep Learning Learning Network, Stochastic Gradient Descent Image Understanding, Language Translation, Voice Recognition, Car driving Connections in artificial neural net P-DMGML PP Pleasingly Parallel (Local ML) Seq /


Digital Signal Processing Instructor: Prof. Peng Yu Tel : 15904510911 : Office : Room 523, Bldg. 2A, Science Park Automatic Test and.

voice mail system voice mail system interactive entertainment systems interactive entertainment systems 2 Basic concepts about system (1) System Device or technology of signal processing. Device or technology of signal processing. (2) Analog system System with analog input and output. System with analog input and output. (3) Digital system System with digital input and output. System/——using MATLAB. Vinay K. Ingle,John G. ProakisISTE Publishing Company,2008 2 Digital Signals Processing——using MATLAB./


Digital Signal Processing Prof. Pengyu Tel : 15904510911 : Office : Room 526, Bldg. 2A, Science Park Automatic Test and Control.

voice mail system voice mail system interactive entertainment systems interactive entertainment systems 2 Basic concepts about system (1) System Device or technology of signal processing. Device or technology of signal processing. (2) Analog system System with analog input and output. System with analog input and output. (3) Digital system System with digital input and output. System/——using MATLAB. Vinay K. Ingle,John G. ProakisISTE Publishing Company,2008 2 Digital Signals Processing——using MATLAB./


Group members Luke Makischuk Abderahmane Sebaa Ameneh Sadat Yazdaninik Asma Faizi Professor: R Habash TA: Wei Yang.

is very complex.  We came up with a simpler way to implement the voice recognition using Matlab and we also expanded more on how you would go about controlling the robot using Bluetooth technology along with motor control of the robot. References  “Speech Recognition and Its Application in Voice-based Robot Control System” by Luo Zhizeng and Zhao Jinghing, August 2004  “A dynamic-time-warp integrated circuit for/


Speech Processing Introduction. 4 September 2015Veton Këpuska2 Syllabus  ECE 5525 Speech Processing  Contact Info: Këpuska, Veton Olin Engineering Building,

Syllabus  Course Goals: Teach modern methods that are used to process speech signals.  Subject Area: Digital Speech/Recognition, Digital Speech Processing for Man-Machine Communication by Voice  Recommended Grading Homework:20% Exams:30% Project(s):50%  MATLAB Exercises and Homework Problems 4 September 2015Veton Këpuska4 Course Information  http://my.fit.edu/~vkepuska/web http://my.fit.edu/~vkepuska/web or Directly  http://my.fit.edu/~vkepuska/ece5525/ http://my.fit.edu/~vkepuska/ece5525/ Angel System/


Concepts of Multimedia Processing and Transmission IT 481, Lecture #1 Dennis McCaughey, Ph.D. 22 January, 2007.

using MATLAB. Project topics will consist of a set of Matlab /recognition possible using only visual information –Integrated with speech recognition systems to improve accuracy Slide: Courtesy, Hung Nguyen 01/22/2007 IT 481, Spring 44 Lip Synchronization Applications –In VTC (video teleconferencing) where video frame is dropped (low bandwidth requirement) but audio must still be continuous –In non-real-time use such as dubbing in studio where recorded voice full of background noise Time-warping commonly used/


29 Sept 09Comp30291 Section 11 Comp30291 Digital Media Processing Barry Cheetham

a human voice. E./Using MATLAB more efficiently SlowFaster 29 Sept 09Comp30291 Section 174 MATLAB/using PCs. Accuracy pre-determined by word-length & sampling rate. Reproducible: every copy of system will perform identically. Characteristics will not drift with temperature or ageing. Availability of advanced VLSI technology. Systems can be reprogrammed without changing hardware. Products can be updated via Internet. DSP systems can perform highly complex functions such as adaptive filtering speech recognition/


ECE 494 Capstone Design Final Design Presentation Smartphone Based Human Behavioral Analysis Andrew Jackson Michael Armstrong Robbie Rosati Andy McWilliams.

of market Many sensors available Open file system Previous Android programming experience Cheaper phone prices 4/Sound Detects sound waves Reports loudness Example: Voice recognition Proximity Changes depending on surrounding objects Boolean/Used MATLAB for data graphing and filtering Light Sensor Test (Different Exposure) 4/18/2014Smartphone Based Human Behavioral Analysis14 Accelerometer Test (Answer Call) 4/18/2014Smartphone Based Human Behavioral Analysis15 XYZXYZ App Development and Activity Recognition/


CMSC Assignment 1 Audio signal processing

location) of the voiced vowel part of x.wav between T1 and T2. Seg1 can be saved as an array in C++ or a vector in MATLAB / OCTAVE . You/matlab to extract the MFCC parameters (Mel-frequency cepstrum http://en.wikipedia.org/wiki/Mel-frequency_cepstrum) from your sound files. Each sound file (.wav) will give one set of MFCC parameters. See “A tutorial of using the htk-mfcc tool” in the appendix of how to extract MFCC parameters. Build a dynamic programming DP based four-numeral speech recognition system. Use/


Www.beckman.uiuc.edu Illinois Group in Star Challenge PART I: visual data processing PART II. Audio Search Liangliang Cao, Xiaodan Zhuang University of.

matlab) Semantic Feature 1: 24 hours (matlab) Semantic Feature 2: 3 hours (c) Semantic Feature 3: 4 hours (c) Motion Feature 1: 24 hours (matlab/ Example: Language-Independent Speech Information Retrieval Voice activity detection Perceptual freq warping Gaussian mixtures/recognition Better performance with language-specific systems than language-independent systems No inter-language mismatch between training and testing (acoustic model, pronunciation model, language model) e.g., for English data, we can use/


Information and Computer Science Department Research Profile Information and Computer Science Department Research Profile Dr. Sadiq M. Sait Information.

ANURBS: The CAD/CAM/CAE Tools. n Automatic Text Recognition: A Need in Arabization, KFUPM, 2001-2005 n /used: Java. Clustering of PCs using PVM. Heterogeneous platforms used. n Processing on the fly was tested by linking the C code of PVM to handle MATLAB applications. n A 16-node Active Network system/using active networks. n To induce routing decisions using active networks. One scenario is to make Link-state protocols stabilize faster. ICS Research Projects: Operating Systems n Natural Language Voice/


A research overview Professor Philip Sallis Auckland University of Technology New Zealand.

etc Geographic Information Systems (GIS) Geographic Information Systems (GIS) Global Positioning Systems (GPS) Global Positioning Systems (GPS) Voice over IP (VoIP) Voice over IP (VoIP) Voice Recognition Voice Recognition Wireless and GPRS/system performance Methods for measuring system performance Profile system users Profile system users Profile system use Profile system use Observe correlations and process dynamics Observe correlations and process dynamics System optimisation & operation management System/


Chapter 1: Introduction to audio signal processing

voice-recognition/ikjmfindklfaonkodbnidahohdfbdhkn?hl=en Audio signal processing Ch1 , v.4b Types depending on speakers Speaker dependent recognition - designed for one speaker who has trained the system. Speaker independent recognition/ Telephone quality speech can be sampled at 8KHz using 8-bit data. Speech recognition systems normally use: 10~16KHz,12~16 bit. Audio signal /Fourier Transform Write pseudo code (or a C/matlab/octave program segment but not using a library function) to transform a signal in/


Characterization Presentation Neural Network Implementation On FPGA Supervisor: Chen Koren Maria Nemets 309326767 Maxim Zavodchik 310623772.

Characters RecognitionVoice Recognition  /Matlab, training and testing it Determining weights length and resolution Determining weights length and resolution Choosing the proper hardware: FPGA and Memory Choosing the proper hardware: FPGA and Memory Planning FSM controller Planning FSM controller Implementing the NN in VHDL Implementing the NN in VHDL Simulation and Synthesis Simulation and Synthesis Performance analysis: hardware vs. software Performance analysis: hardware vs. software System/using/


Speech Signal Processing I By Edmilson Morais And Prof. Greg. Dogil Stuttgart, October 18, 2001.

systems - TTS Waveform generation for TTS systems - TTS Automatic Speech Recognition (Statistical approach)- ASR Automatic Speech Recognition (Statistical approach)- ASR Fundaments of programing in Matlab Fundaments of programing in Matlab It will be the tool used for our simulations It will be the tool used/– LP coeficients e – LP residue En – Prototypes Fo – Fundamental frequency U/UV – Voiced / Unvoiced transitions TTS - Waveform generation for TTS Speech coding Speech coding Parametric coders, Waveform /


Chapter 4: Pitch estimation for music signal processing

because is at . Ch4. pitch, v4b Testing a real sound A5_flute 880Hz, (sampling at fs=44100Hz) %testing a real sound , matlab code %x=[1 3 7 2 1 9 3 1 8 ], [xx,fs,nbits]=wavread(c:soundsA5_flute.wav); sound(x,fs)%fs=44100Hz/ voice pitch detection (or recognition ) We must study its structure of the vocal system and find out how to get the accurate answer. vocal system has 2 elements Glottal excitation (no use for pitch measurement) Vocal tract filter Use liftering to remove glottal excitation before we use /


“Speech Signal Processing’

recognition systems of speaker changes, check if a user is already enrolled in a system Speaker identification problems generally fall into two categories: Differentiating multiple speakers when a conversation is taking place. Identifying an individuals voice based upon previously supplied data regarding that individuals voice. Speaker identification is based on complex voice processing algorithms. Text-independent systems are most often used/ the TMS320VC5510 using C++ and MATLAB and illustrate concepts/


ECE 260B – CSE 241A Intro and ASIC Flow.1http://vlsicad.ucsd.edu ECE260B – CSE241A Winter 2005 Introduction and ASIC Flow Instructor: Bao Liu Website:

Recognition Sentence Translation GOPS: Giga Operations Per Second 100 Voice Auto Translation 10Mpps 100Mpps MPEG4 Face Recognition Voice Print Recognition SW Defined Radio Moving Picture Recognition/and ASIC Flow.26http://vlsicad.ucsd.edu System Complexity Challenges  System Complexity = exponentially increasing transistor counts, /Design Procedure and Tools  Behavior modeling l Matlab/C/VHDL  Logic synthesis l DesignCompiler, / analysis algorithms similar to those used during the static timing analysis /


Module Overview. Aims apply your programming skills to an applied study of Digital Image Processing, Digital Signal Processing and Neural Networks investigate.

exam weighted at 70% Engineers and scientists would normally use Matlab – but Software Engineers need to be able to write the code (someone wrote Matlab). Done mainly in lab and assignment Top-down approach:/scanning / photo Limbs –Fingerprint recognition –Gesture interpretation –Lip reading –Handwriting Voice –Speech recognitionVoice identification Others… ? Some output technologies Audible –Speech synthesis –Spatial awareness Visual –Graphical display Others…? General systems We live in an analogue /


2015/6/281 MIR: Status and Trends 音樂資訊檢索的現況與未來 J.-S. Roger Jang ( 張智星 ) Multimedia Information Retrieval Lab CS Dept., Tsing Hua Univ., Taiwan

(with demos) yQuery by singing/humming (QBSH) ySinging voice separation zConclusions -3- Types of MIR Systems zText-based MIR yText input x 歌名、歌手、歌詞、作 詞者、作曲者 xMetadata: /.org/jang/matlab/toolbox/sap)http://mirlab.org/jang/matlab/toolbox/sap xgoPtbyAcf/classification/retrieval zPreexisting approaches shed lights on MIR. ySpeech recognition/synthesis yText information retrieval yMusic theory -36- References / Chen, and J.-S. R. Jang, "On the Use of Anti-word Models for Audio Music Annotation and Retrieval", IEEE/


Sound Controlled Smoke Detector Group 67 Meng Gao, Yihao Zhang, Xinrui Zhu 1.

Arduino if fire hazard is detected Capture voice and analyze the feature Turn off fire/Over 500 clap sound clips collected in lab Use python to implement data training algorithm 25 Cooking / fire detector work Successfully implemented Speech Recognition on Matlab 26 Future Work Hardware Improve LPF accuracy/Matlab Web resource, available: http://www.ee.columbia.edu/~dpwe/resources/matlab/dtw/.http://www.ee.columbia.edu/~dpwe/resources/matlab/dtw/ [4]”8-bit Atmel Microcontroller with 16/32/64KB In-System/


D EPARTMENT OF E LECTRONICS & C OMMUNICATION E NGINEERING National Institute of Technology Calicut.

using HVS models Secure Communication – Design of Hardware efficient Secure communication systems Speech Recognition – Audio-visual speech recognition/FACILITIES IN SIGNAL PROCESSING LAB Software Tools: MATLAB LAB VIEW Multisim (Circuit simulation software) /systems 4.Real Time Voice encryptor on a digital signal processor 5.Fingerprint matching 6.FPGA Implementation of Elliptic Curve Cryptosystems 7.Echo Cancellation Using Adapted Filterbank 8.Wavelet based image compression schemes using human vision system/


Software defined radio to enable NNEC: Technical challenges and opportunities for NATO Dr Michael Street NATO UNCLASSIFIED.

STANAGs for terrestrial radio) Plus national and proprietary systems Interoperability problem for multi-national forces SDR decouples / library Technical issues are probably easiest to resolve Languages used C, C++, Matlab, Python DSP, VHDL, Obj ? Structure of code/ – to complete part of HF house STANAG 4591 – for voice service Full content, see paper on waveform library … Rational assessment / SDR Growing recognition of testing Lessons learned from other NATO programmes E.g. SCIP Recognition that testing /


P. 1 DSP-II Digital Signal Processing II Marc Moonen Dept. E.E./ESAT, K.U.Leuven homes.esat.kuleuven.be/~moonen/

Systems vs. Digital Systems - translate analog (e.g. filter) design into digital - going `digital’ allows to expand functionality/flexibility/… (e.g. how could analog speech recognition/. Algebra, 1ste kand !!!) –Channel model is then used to design suitable equalizer (`channel inversion’), or (better/1 Introduction DSP in applications : ADSL Telephone Line Modems –voice-band modems : up to 56kbits/sec in 0..4kHz /’ …to support slides/course notes 6 Matlab/Simulink Sessions …to support homeworks …come prepared/


Computational Intelligence for Biometric Applications Vincenzo Piuri Università degli Studi di Milano, Italy In cooperation with Ruggero Donida Labati,

a prototype of the methodology EER, zeroFMR, zeroFNMR. Matlab Rule-based system © 2015 Vincenzo Piuri 47/48 Conclusions Biometric systems are critical for security Biometric systems are critical for security Aspects in different technological areas / Iris Recognition", IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol.37, no.5, pp.1167-1175, October 2007. V. Piuri, and F. Scotti, "Adaptive Reflection Detection and Location in Iris Biometric Images by Using Computational /


Computational Auditory Scene Analysis DeLiang Wang Perception & Neurodynamics Lab Department of Computer Science and Engineering The Ohio State University.

, and use marginal distribution P(X r |C) in recognition Require a T-F mask to indicate reliable regions, which can be supplied by a CASA system It provides/Binaural segregation produces better results than monaural segregation It works equally well for voiced and unvoiced speech Binaural segregation employs spatial cues, whereas monaural segregation exploits /.cse.ohio-state.edu/pnl Sheffield University has a webpage for the Matlab Auditory Demonstrations from http://www.dcs.shef.ac.uk/~martin/MAD/docs/mad/


Scott Settembre CSE 734 : Cyber Physical Spaces

Similarity must exceed a particular threshold Higher threshold produces more false negatives Lower threshold produces more false positives Voice variability and security issues make this a difficult threshold value to determine (more later) March 16, 2009/] Scott Settembre [ss424@cse.buffalo.edu] Recognition Methods Text Dependent Requires user to speak text spoken at enrollment Usually a name, password, or phrase Text Prompting is used to combat deception The system requires the user to repeat back a random/


EG-348_371_09 1 Multimedia Communications (371) Speech and Image Communications (348) John Mason Engineering Swansea University.

Recognition  Speech & Speaker  How ?  Frame-based  Systems approach EG-348_371_09 9 Some Books  Flanagan -’Speech Analysis, Synthesis and Perception’, Springer-Verlag, - a classic!  Furui - several books on recognition  Parsons - `Voice and/H(z) Thus Analysis must derive these parameters, and Synthesis must use them to re-generate speech EG-348_371_09 27 Principle of linear / s n-i s n-p +-+- Note – minus sign: in Matlab combined with a i What determines p? Original Speech Residual EG-348_371_09 44/


Software Defined Radio -Introduction 성균관대학교 성균관대학교정보통신공학부조준동 6.25 2002 © 스마트 파워 모빌 컴퓨팅 Lab. 1.

voice (SCO) support. Data (ACL) and voice/system Resident compilers and/or real-time standard operating system 36 IT-SOC2002 © 모빌 컴퓨팅 설계자동화 Lab Who uses/Reconfigurable Platform by Hartenstein 응용분야 : pattern recognition, image processing, SDR and encryption 응용분야 : pattern recognition, image processing, SDR and encryption Fine /systems.html) 4. Heron 사 (http://www.traquair.com/catalog/heron.systems.html)http://www.traquair.com/catalog/heron.systems.html 5. Matlab:Sigmal-master (http://www.kimhua.co.kr) 5. Matlab/


... NOT JUST ANOTHER PUBLIC DOMAIN SOFTWARE PROJECT... UAB – CIS Joseph Picone Inst. for Signal and Info. Processing Dept. Electrical and Computer Eng.

Evaluations Ease of Use Lightweight Programming Efficiency: Memory Hyper-real time training Parallel processing Data intensive Research: Matlab Octave Python ASR/SYSTEMS FOR THE CAR APPLICATIONS SPEAKER RECOGNITION Voice verification for calling card security First wide-spread deployment of recognition technology in the telephone network Extension of same statistical modeling technology used in speech recognition APPLICATIONS SPEAKER STRESS AND FATIGUE Recognition of emotion, stress, fatigue, and other voice/


Anil Alexander 1, Oscar Forth 1, Marianne Jessen 2 and Michael Jessen 3 1 Oxford Wave Research Ltd, Oxford, United Kingdom 2 Stimmenvergleich, Wiesbaden,

Florida, USA July 22 nd 2013 VOCALISE New system for forensic speaker recognition called VOCALISE - Voice Comparison and Analysis of the Likelihood of Speech Evidence Provides the capability to perform comparisons using ‘Automatic’ spectral features ‘Traditional’ forensic phonetic parameters/you could average or use other measures Major impediment to incorporating more phonetics into the LR framework is the lack of appropriate and user-friendly tools Requires dedicated knowledge of Matlab and R Other /


FACULTY IN THE DEPARTMENT OF ELECTRICAL ENGINEERING Presented to the: EE 1001 Introduction to Electrical Engineering Class by Stan Burns Professor Department.

of results Using Matlab, or Mathematica. Many Matlab toolboxes are available on most Labs Computers. 4 Research Interests Mainly Include the Following Fields: 1. Signal Processing 2. Image Processing 3. Pattern Recognition: Face & Voice Recognition, Signature / Projects 4 Electronic Stethoscope with Diagnostic Capability 4 Automated Meter Reading Architecture using Wireless Paging Technology 4 Facial Recognition System for Biometric Security Implementation 4 Wireless Cell Phone Charger Taek Mu Kwon Professor/


Introduction to Biometrics Dr. Bhavani Thuraisingham The University of Texas at Dallas Lecture #7 Biometric Technologies: Finger Scan September 14, 2005.

http://www.mathworks.com/products/image/ http://www.mathworks.com/products/image/ - Matlab Image Processing - Matlab available in some of our labs - Cannot download l CMU Voice Recognition Open Source System Sphinx - http://cmusphinx.sourceforge.net/html/cmusphinx.php http://cmusphinx.sourceforge.net/html/cmusphinx.php Face Recognition l Given at CMU, involves face recognition using neural networks. l 32 images of each of 20 students in the/


FACULTY IN THE DEPARTMENT OF ELECTRICAL ENGINEERING Presented to the: EE 1001 Introduction to Electrical Engineering Class by Stan Burns Professor Department.

of results Using Matlab, or Mathematica. Many Matlab toolboxes are available on most Labs Computers. 4 Research Interests Mainly Include the Following Fields: 1. Signal Processing 2. Image Processing 3. Pattern Recognition: Face & Voice Recognition, Signature / Projects 4 Electronic Stethoscope with Diagnostic Capability 4 Automated Meter Reading Architecture using Wireless Paging Technology 4 Facial Recognition System for Biometric Security Implementation 4 Wireless Cell Phone Charger Taek Mu Kwon Professor/


© 2000 Altera Corporation 3rd Generation Wireless Technical Solutions Seminar.

/3 Soft decision decoding Used to give BER 10 -3 for voice 3G Specification Decoder Control /Recognition of Symmetrical, Non-Symmetrical and Anti-Symmetrical Filters –Automatic interpolation and decimation filters Provides resource estimates dynamically Creates MATLAB/MATLAB - Simulink Interface FIR compiler generates Simulink models based on parameters entry Speeds up DSP system-level analysis © 2000 Altera Corporation 128 NCO Compiler © 2000 Altera Corporation 129 Digital NCO Compiler An NCO May Be Used/


FACULTY IN THE DEPARTMENT OF ELECTRICAL ENGINEERING Presented to the: EE 1001 Introduction to Electrical Engineering Class by Stan Burns Professor Department.

of results Using Matlab, or Mathematica. Many Matlab toolboxes are available on most Labs Computers. 4 Research Interests Mainly Include the Following Fields: 1. Signal Processing 2. Image Processing 3. Pattern Recognition: Face & Voice Recognition, Signature / Projects 4 Electronic Stethoscope with Diagnostic Capability 4 Automated Meter Reading Architecture using Wireless Paging Technology 4 Facial Recognition System for Biometric Security Implementation 4 Wireless Cell Phone Charger Taek Mu Kwon Professor/


FACULTY IN THE DEPARTMENT OF ELECTRICAL ENGINEERING Presented to the: EE 1001 Introduction to Electrical Engineering Class by Stan Burns Jack Rowe Chair.

of results Using Matlab, or Mathematica. Many Matlab toolboxes are available on most Labs Computers. 4 Research Interests Mainly Include the Following Fields: 1. Signal Processing 2. Image Processing 3. Pattern Recognition: Face & Voice Recognition, Signature / Projects 4 Electronic Stethoscope with Diagnostic Capability 4 Automated Meter Reading Architecture using Wireless Paging Technology 4 Facial Recognition System for Biometric Security Implementation 4 Wireless Cell Phone Charger Taek Mu Kwon Professor/


Sharif University of Technology Department of Computer Engineering Side Channel Attacks through Acoustic Emanations Presented by: Amir Mahdi Hosseini Monazzah.

keyboard and then use it to attack another keyboard of the same type  There is a reduction in the quality of recognition  The /Create more accurate information NoYes Motivational Example  Capturing the voice of pressing ‘h’ key  Capturing the voice of pressing ‘z’ key Introduction Preliminaries Keyboard … /Keyboard … Simulation … Conc. … 16 Side Channel Attacks through Acoustic Emanations System Setup (Cont.)  This Study  MATLAB neural network simulator  Simple PC microphone for short distances  up to/


P. 1 DSP-II Digital Signal Processing II Marc Moonen Dept. E.E./ESAT, K.U.Leuven homes.esat.kuleuven.be/~moonen/

Systems vs. Digital Systems - translate analog (e.g. filter) design into digital - going `digital’ allows to expand functionality/flexibility/… (e.g. how would you do analog speech recognition/Introduction DSP in applications : ADSL Telephone Line Modems –voice-band modems : up to 56kbits/sec in 0/ in upstream, downstream in downstream) Meaning that a useful signal may be drowned in (much larger) signals / `Homeworks’ …to support course material 6 Matlab/Simulink Sessions …to support homeworks …come prepared/


Aibo companion DOAS – group 1 Aitor Azcarate Onaindia Abeer Mahdi Zhiwei Zhan Ning Yang Supervisor: Frans Groen.

(c++ programming) – Tekkotsu (c++, java and matlab) – Remote framework (combined with visual c++) – R-code (script language, which we used) Graphic user interface – Motion editor (creating new motions for Aibo) Control panel – Sony entertainment player (control Aibo) Reaction to sound Aibo has a predefined voice command recognition list of 54 voice commands We implemented some reactions to certain voice commands, some of these reactions are motions/


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