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Copy of Final Year Project: Voice Recognition system using MATLAB

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hasan alii

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Transcript of Copy of Final Year Project: Voice Recognition system using MATLAB

By : Hasan M.Ali Hamedan (M021020009) Developing feature extraction algorithm for automatic voice detection and identification INTRODUCTION RESULT AND ANALYSIS by :
Yusherizan Marshella Binti Yusoh
(EE084076) Literature Review Steps to construct the Voice Recognition System:

Prepare a speech database for training and testing.

Voice processing.

Training speech database.

Simulation and evaluation. RESULT AND ANALYSIS OBJECTIVES To evaluate the performance of different Technique (Mel-Frequency Cepstral Coefficients (MFCCs),perceptual linear prediction Coefficients (PLP) and linear prediction Coefficients (LPC) of feature extraction algorithm for automatic voice detection and identification.

Design Voice identification model that is capable of identifying the trained subject from not trained.

Design Voice verification model that could accept or reject the trained subject from not trained subject accurately.

Implement the design models using Matlab software Voice Database for Training and Testing Create voice database for references to make comparison later on.

Voice database recorded using Microsoft WAV format.

Create database for the TRAIN folder and TEST folder.

The voice model will be trained in (MFCC,PLP and LPC) vector space for each speaker.

After the training steps, system should be able to acknowledge the voice characteristic for each speaker.

Testing phase, system will identify the speaker of each sound file in TEST folder. Voice Processing Voice Processing The speech signal(vector) will be cut into frames. Result of cutting will be a matrix of N samples from original voice.

Applying windowing and FFT to transform the signal into frequency domain (spectrum or periodogram)

Compute power spectrum using imagesc command.

Converting power spectrum into MFCC. Voice Processing Experimental results SIMULATION AND EVALUATION Simulate the training and testing procedure for the voice recognition system. Technique chosen for Feature Extraction and Feature Matching Feature Extraction:
Mel Frequency Ceptrum Coefficient (MFCC)
Perceptual linear Prediction Coefficients (PLP)
Linear Prediction Coefficients (LPC)

Feature Matching:
Gaussian mixture model (GMM) METHODOLOGY Voice Recognition System: Process of automatically recognizing who is the spaeker based on the unique characteristics contained in speech waves.

System implemented as security features for:
-Building acces
-Credit card Verification

Two elemets in Voice Recognition System:
– Feature Extraction: Process of extracting
unique information from speech files.
– Feature Matching: Process of identifying the
speaker that involves comparing unknown
data. Supervisor: MOHD SAEED JAWAD OVERVIEW INTRODUCTION
-Objective
-Literature Review
-Methodology

RESULT AND ANALYSIS

CONCLUSION UNIVERSITI TEKNIKAL MALAYSIA MELAKA
Faculty of Electronics and Computer Engineering (FKEKK) Literature Review
previous work Voice identification Voice verification Robust voice detection and identification system should be effective under full variation in: environmental conditions, speaker variability.

Heavily speaker dependent

Continuous speech recognition.

Reduce computational time for voice detection and identification algorithm.

Problem staement Introduction Multimedia (audio-visual contents) associated with speech is continuously growing and filling our computers, networks and lives
Such as broadcast news, lectures, shows, voice mails, (contact-center) conversations, etc.

On the other hand, speech is the primary and the most convenient means of communication between people
Speech provides a better (or natural) user interface in wireless environments and especially on smaller hand-held devices.

Speech will be the key for multimedia information access in the near future .

The human speech contain numerous discriminative features that can be used to identify speakers.
CONCLUSION Improvement can be implement in the Voice Recognition System according to the application.

The experimental results indicates that the PLP feature extraction has the best accuracy comparing to the other approaches (MFCC and LPC).

Application that utilize the Voice recognition system:
-Time and attendance system
-Telephone-Banking
– Home Automation
– For disabilities people
[1] M.A.Anusuya and S.K.Katti “ Speech Recognition by Machine: A Review” International Journal of Computer Science and Information Security, Vol. 6 ( 3) 2009

[2] Tsang-Long Pao, Wen-Yuan Liao, Tsan-Nung Wu, Ching-Yi Lin “ Automatic Visual Feature Extraction for Mandarin Audio-Visual Speech Recognition’ Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics San Antonio, TX, USA – October 2009.

[3] Santosh K.Gaikwad, Bharti W.Gawali and Pravin Yannawar, “A Review on Speech Recognition Technique”, International Journal of Computer Applications (0975 – 8887) Volume 10– No.3, November 2010

[4] Vimala.C and V. Radha “A Review on Speech Recognition Challenges and Approaches” World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 2, No. 1, 1-7, 2012
[5] Wiqas Ghai Khalsa College (ASR) of Technology & Business Studies, Mohali, Punjab Navdeep Singh Mata Gujri College, Fatehgarh Sahib, Punjab
Literature Review on Automatic Speech Recognition Wiqas Ghai , International Journal of Computer Applications (0975 – 8887) Volume 41– No.8, March 2012

Refrences [5] [2] [4]

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  • Copy of Copy of Copy of Final Year Proje…

    Copy of Copy of Copy of Final Year Project: Voice Recognition system using MATLAB

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    Copy of Copy of Final Year Project: Voice Recognition system using MATLAB

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    Speaker Recognition Using MFCC and Vector Quantization Model
     A Major Project Report
    Submitted in Partial Fulfillment of the Requirements  for the Degree of 
    Bachelor O
    F
    T
    ECHNOLOGY
     I
    N
     ELECTRONICS
     
    &
     
    COMMUNICATION
     
    ENGINEERING
    By DARSHAN MANDALIA (07BEC042)PRAVIN GARETA (08BEC156)Under the Guidance of Prof. RACHNA SHARMA
    Department of Electrical EngineeringElectronics & Communication Engineering ProgramInstitute of Technology,
     
    NIRMA UNIVERSITY 
     
     A 
    HMEDABAD
    382 481May 2011

     

    CERT CERT CERT CERTIFICATE IFICATE IFICATE IFICATE 
    This is to certify that the Major Project Report entitled
    “Speaker RecognitionUsing MFCC and Vector quantization model”
    submitted by
    Pravin Gareta(
    Roll No.
    08BEC156)
    and
    Darshan Mandalia
    (Roll No.
    07BEC042
    ) as the partialfulfillment of the requirements for the award of the degree of 
     Bachelor of Technology
    in Electronics & Communication Engineering, Institute of Technology,
    Nirma University
    is the record of work carried out by them undermy supervision and guidance. The work submitted in our opinion has reached alevel required for being accepted for the examination.
    Date: 17/05/2011
    Prof. RACHNA SHARMAProject GuideProf. A. S. RanadeHOD (Electrical Engineering)Nirma University, Ahmedabad
     

     

    i
    Acknowledgement
    In order to achieve better performance, we should have to learn our outside environment. There arelots of forces which will acting upon us to get the better result, but for that we have to change ourattitude to see them. There are lots of problems we facing, but due to it we don’t stop. It is not a goodhuman being ,if he is stop. Yes, we are sometimes frustrated due to the problems we can’t solve it.But the next day we act on the problem with same efficiency and strength we have. Moreover, Weare highly thankful to our parents and teachers were there all the times, backing us up and with theirundue support has been the pushing drive for us to complete project within time.We would deeply like to express our sincere gratitude towards project guide Prof. Rachna Sharmaand faculty members of our panel who have guided until the completion of the project. We alsoextend our thanks towards our Head of the Department Prof. A.S.Ranade and all the staff,Department of Electronics and Communication Engineering, the Institute of Technology, NirmaUniversity for their assistance during the project whether it was a technical help or concerned withproviding facilities for internet, implementing and simulating the ideas of the project. Their excessivesupport has been the source of motivation to perform our best regarding the project.We would like to express our gratitude towards our parents who have been there not only in thisproject but through all our entire life. If their helping hand, moral as well as financial support, had notbeen there we wouldn’t have been able to finish in such a proficient way. We are grateful for their aidand support.
    Pravin Gareta (08BEC156)Darshan Mandalia (07BEC042)

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    Speaker Recognition Using MATLAB

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    In this project using matlab as a tool for simulation we have made 3 codes (1)MFCC apprich (2)FFT approch (3) VQ approch

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    Speaker Recognition Using MATLAB

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    Uploaded by Pravin Gareta
    In this project using matlab as a tool for simulation we have made 3 codes (1)MFCC apprich (2)FFT approch (3) VQ approch
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    Speaker Recognition Using MATLAB

    Uploaded by Pravin Gareta

    Related Interests

    • Speech Recognition
    • Speech Synthesis
    • Signal Processing
    • Psychology & Cognitive Science
    • Cognitive Science

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    Description: In this project using matlab as a tool for simulation we have made 3 codes (1)MFCC apprich (2)FFT approch (3) VQ approch
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    In this project using matlab as a tool for simulation we have made 3 codes (1)MFCC apprich (2)FFT approch (3) VQ approch
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