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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4787
VOICE MODULATION AND VERIFICATION FOR SMART
AUTHENTICATION SYSTEM
S. VISHNUPRIYA1, J. SUJATHA2
1PG Scholar, Department of MCA, Arulmigu Meenakshi Amman College of Engineering, Anna University,
Vadamavandal (near Kanchipuram), India.
2Assistant professor, Department of MCA, Arulmigu Meenakshi Amman College of Engineering, Anna University,
Vadamavandal (near Kanchipuram), India.
----------------------------------------------------------------------***---------------------------------------------------------------------
ABSTRACT:- Biometric is physical characteristic unique to each individual. It has a very useful application in authentication
and access control. The designed system is a text-prompted version of voice biometric which incorporates text-independent
speaker verification and speaker-independent speech verificationsystemimplementedindependently.Thefoundationforthis
joint system is that the speech signal conveys boththespeechcontentandspeakeridentity.Suchsystemsare more-securefrom
playback attack, since the word to speak during authentication is not previously set. During the course of the project various
digital signal processing and pattern classification algorithms were studied. Short time spectral analysis was performed to
obtain MFCC, energy and their deltas as feature. Feature extraction module is same for both systems. Speaker modelling was
done by GMM and Left to Right Discrete HMM with VQ was used for isolated word modelling. And resultsofbothsystemswere
combined to authenticate the user. The speech model for each word was pre-trained by using utterance of 45 English words.
The speaker model was trained by utterance of about 2 minutes each by 15 speakers. While uttering the individual words,the
recognition rate of the speech recognition system is 92 % and speaker recognition system is 66%. For longer duration of
utterance (>5sec) the recognition rate of speaker recognition system improves to 78%.
1. INTRODUCTION
A Text involvesTraditional andScientific Methods
to improve the quality of the Text to voice recognition.
Scientific methods of Text training need to be introduced
for further improvement with our present day empirical
methodology. The process of enriching the Text is known
as Text culture. It involves training the Text to sing or
speak in a particular desired way. It is a procedure where
one learns to master one‘s Text. This study includes
traditional and scientific methods to improvethequalityof
Text. Fundamentally Text culture refers to the
methodology adapted to train or control the Text to sing
effectively. The dynamism, perfect control and freedom of
the Text and the uplifting and inspiring effect of the
performance. The entire vocalizing mechanism involves
coordinated action of various muscles initiated by the
brain combined with a sense of purpose to express a
thought or idea.―Text culture is the coming together of an
understanding of science (to a high degree) with the
physical feel of the Text. We will have to understand the
terms anchoring, focusing, erection and fusion of the Text
itself.
2. SYSTEM ANALYSES
2.1 Existing System
Currently the viable authentication mechanisms is use are
password or PIN based. A user wishers to beauthenticated
enters a short string or a number which is supposedlyeasy
to remember, but is easy to forget and the authenticating
machine checks the hash of the password against a stored
hash in a database. If a user were to forget his or her
password or it was stolen by someone wishing to steal the
user’s identities of the user becomes endangered and easy
to compromise. A common solution to the problem is to
implement a biometric authentication mechanism such as
retina scans or fingerprint based authentication. The
advantage of this a retina or a fingerprint cannot be
forgotten and it is unique to each user. Whilesucha system
us extremely difficult to compromise, the cost of
implementation restricts its development. In addition, if
such biometric data was in fact compromised, the result
would be disastrous for the user- he or she cannot change
fingerprints or retinas.
2.2 Proposed System:
The system proposed to solve both theproblemof
password based authentication and biometric
authentication is via Text Verification Using Back
Propagation. The hardware necessary for Text
verification is inexpensive and it can be deployed in (E.g.
credit card machines in stores, tablet PCs, ATM
machine).The system is proposed to overcome
authenticating problem in Text verification withthehelp
of Back propagation Algorithm. Any person in this world
can never sign a same Text every time in their life time.
His/her Text will be differing from time to time. When
the user is in a calm mood the Text will be very different
than the Text of the same user in a hurry or in a bad
mood. So to overcome this problem Back propagation
Algorithm this is one of the best neural network
techniques to train the artificial neuron to recognize the
different type of Text of same user. If the neurons are
fine-tuned they can provide us the best authentication
security.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4788
3. SOFTWARE REQUIREMENT SPECIFICATIONS
3.1 Introduction to .NET Framework
 The Microsoft .NET Framework is a software
technology that is available with several software
windows operating systems.
 It includes a large library ofpre-codedsolutionsto
common programming problems and a virtual
machine that manages the execution of the
programs written specifically for the framework.
 The pre-coded solutions that form the
framework’s Base Class Library cover a large
range of programming needs ina numberofareas,
including user, interface, data access, database
connectivity, cryptography, web application
development, numeric algorithms and network
communications.
 The class library is used by programmers, who
combine if with their own code to produce
applications.
 Programmers written for the .NET framework
executes in the software environment that
manages the program’s runtime requirements.
Also part of the .NET framework, this runtime
environment is known as the common Language
Runtime (CLR).
4. SYSTEM IMPLEMENTATION:
4.1 USER DETAILS MANAGEMENT:
In this module user details along with user original
Text is stored in the database. The Text will beconvertedinto
binary format & stored as OLE objectindatabase.Initiallythe
variance for comparison is set to an acceptable value. All the
database operations are doneinSQL usingstoredprocedures
concept.
4.2 TEXT CAPTURING:
4.4 TEXT RETIEVAL FROM DATABASE
4.4.1 LEARNING TEXT
In this module a new Text is got from user as input,
after that Text is processed as follows. The number of Text
strokes, timing of strokes, Text proportions and stroke
length. If any of the process results in variance less than the
initial variance, then absolute difference are calculated
between the new variance and initial variance. If the error or
difference is not minimized to a value, the average is taken
between new and initial variance. This average is taken as a
input variance for another new Text. Again the difference is
calculated if the error is not minimized the above process is
repeated until error is minimized. The application user must
stop only if he is satisfied with the result. If the error is
minimized final variance and last error is stored in database,
for next phase of verifying Text.
4.4.2 TEXT PROPORTION VERIFICATION
The Text proportion we use both the height and
width will be checked. For finding the height and width of
the Text it use the Get Bounding Box () method. This
method return the height and width value of the Text. This
method returns the height and width of every node in the
Text. Using the height and width oftheTexttheverification
is done separately for height of the Text and the width of
the Text separately.
4.4.3 TEXT PROPRTION IN WIDTH
The width of the both the Text is found using the
GetBoundingBox() method and by combining the width of
two Text the output variance will be calculated and this
output variance is compared with the input variance and if
the output variance is greater than input variance then the
Text is rejected.
4.4.4 TEXT PROPRTION IN HEIGHT
The Height of the both the Text is found using the
GetBoundingBox() method and by combining the width of
two Text the output variance will be calculated and this
output variance is compared with the input variance and if
the output variance is greater than input variance then the
Text is rejected.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4789
4.5 Modulation Techniques
The Communications Toolbox™ supports
modulation these techniques for digital data. All the
methods at the far right are implemented in library blocks.
Like analog modulation, digital modulation alters a
transmittable signal according to the information in a
message signal. However, for digital modulation the
message signal is restricted to a finite set. Modulation
functions output the complex envelope of the modulated
signal. Using the Communications Toolbox, you can
modulate or demodulate signals using various digital
modulation techniques, and plot signal constellations.
5. UML DIAGRAM
UML standsforUnifiedModelingLanguage.UMLis
a standardized general-purpose modeling language in the
field of object-orientedsoftwareengineering.Thestandard
is managed, and was created by, the Object Management
Group. The goal is for UML to become a common language
for creating models of object oriented computer software.
In its current form UML is comprised of two major
components: A Meta-model and a notation. In the future,
some form of method or process may also be added to or
associated with UML. The Unified Modeling Language is a
standard language for specifying, Visualization,
Constructing and documenting the artifacts of software
system, as well as for business modeling and other non-
software systems. The UML represents a collection of best
engineering practices that have proven successful in the
modeling of large and complex systems. The UML is a very
important part ofdeveloping objectsorientedsoftwareand
the software development process. The UML uses mostly
graphical notations to express the design of software
projects.
5.1 ER DIAGRAM:
5.2 CLASS DIAGRAM:
In software engineering, a class diagram in the Unified
Modeling Language (UML) is a type of static structure
diagram that describes the structure of a system by
showing the system's classes, their attributes, operations
(or methods), and the relationships among the classes. It
explains which class contains information.
5.3 SEQUENCE DIAGRAM:
A sequence diagram in Unified Modeling Language
(UML) is a kind of interaction diagram that shows how
processes operate with one another and in what order. It
is a construct of a Message Sequence Chart. Sequence
diagrams are sometimes called event diagrams, event
scenarios, and timing diagrams.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4790
6. SYSTEM TESTING
Testing virtual to the success of the system.
System testing makes logical assumption that if all the
parts system are correct, the goal will be successfully
achieved. This system is tested by following test cases and
prepared for final implementation.
6.1 TYPES OF TESTING
6.2.1 UNIT TESTING
Unit testing involves the design of test cases that
validate that the internal program logic is functioning
properly, and that program input produces valid outputs.
All decision branches and internal code flow should be
validated. It is the testing of individual softwareunitsofthe
application. It is done after the completion of an individual
unit before integration. This is a structural testing, that
relies on knowledge of its constructionandisinvasive.Unit
tests perform basic tests at component level and test a
specific business process, application, and/or system
configuration. Unit tests ensure that each unique path of a
business process performs accurately to the documented
specifications and contains clearly defined inputs and
expected results.
6.2.2 INTEGRATION TESTING
Integration tests are designed to test integrated
software components to determine if they actually run as
one program. Integration tests demonstrate that although
the components were individually satisfaction, as shown
by successfully unit testing, the combination of
components is correct andconsistent.Integrationtestingis
specifically aimed at exposing the problemsthatarisefrom
the combination of components.
6.2.3 FUNCTIONAL TESTING
Functional tests provide systematic demonstrations
that functions tested are available as specified by the
business and technical requirements, system
documentation and user manuals.
6.2.4 SYSTEM TESTING
System testing ensures that the entire integrated
software system meets requirements. It tests a
configuration to ensure known and predictable results.An
example of system testing is the configuration oriented
system integration test. System testing is based on process
descriptions and flows, emphasizing pre-driven process
links and integration points.
6.2.5 WHITE BOX TESTING
White Box Testing is a testing in which in which the
software tester has knowledge of the inner workings,
structure and language of the software, or at least its
purpose. It is purpose. It is used to test areasthatcannot be
reached from a black box level.
6.2.6 BLACK BOX TESTING
Black Box Testing is testing the software without any
knowledge of the inner workings, structure or language of
the module being tested. Black box tests, as most other
kinds of tests, must be written from a definitive source
document, such as specification or requirements
document, such as specification or requirements
document. It is a testing in which the software undertestis
treated, as a black box .you cannot “see” into it. The test
provides inputs and responds to outputs without
considering how the software works.
6.2.7 ACCEPTANCE TESTING
User Acceptance Testing is a critical phase of any
project and requires significant participation by the end
user. It also ensures that the system meets the functional
requirements.
Functional testing is centered on the following items:
Valid Input : identifiedclassesofvalid
input must be accepted.
Invalid Input : identified classes of
invalid input must be rejected.
Functions : identifiedfunctionsmust
be exercised.
Output : identified classes of
application outputs must be exercised.
Systems/Procedures.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4791
7. OTHER TESTING METHODOLOGIES
7.1 User Acceptance Testing
User Acceptance of a system is the key factor for
the success of any system. The system underconsideration
is tested for user acceptancebyconstantlykeepingintouch
with the prospective system users at the time of
developing and making changes wherever required. The
system developed provides a friendly user interface that
can easily be understood even by a person who is new to
the system.
7.2 Output Testing
After performing the validation testing, the next
step is output testing of the proposed system, since no
system could be useful if it does not produce the required
output in the specified format. Asking the users about the
format required by them tests the outputs generated or
displayed by the system under consideration. Hence the
output format is considered in 2 ways – one is on screen
and another in printed format.
7.3 Validation Checking
Validation checks are performed on the following
fields.
7.4 Text Field:
The text field can contain only the number of
characters lesser than or equal to its size. The text fields
are alphanumeric in some tables and alphabetic in other
tables. Incorrect entry always flashes and error message.
7.5 Numeric Field:
The numeric field can contain only numbersfrom
0 to 9. An entry of any character flashes an error messages.
The individual modules are checked for accuracyandwhat
it has to perform. Each module is subjected to test run
along with sample data. The individually tested modules
are integrated into a single system. Testing involves
executing the real data information is used in the program
the existence of any program defect is inferred from the
output. The testing should be planned so that all the
requirements are individually tested.
A successful test is one that gives out the defects
for the inappropriate data and produces and output
revealing the errors in the system interfacing systems or
procedures must be invoked.
8. CONCLUSION
In this project, I have presented an exercise survey of
smart authentication system, I have categorized the
modules in speaker recognition and discussed different
approaches for each module. In addition to this, I have
presented study of the various typical searchbeingcarried
out in the field of speaker recognition. I have also
discussed issued and challenges pertaining to the speaker
recognition system and face recognition system for smart
authentication systems.And alsoIdidsmartauthentication
for large sectors for security purpose. This project is used
for security or Network Security by the coming generation
to used this security system.
9. FUTURE ENHANCEMENT
The purpose of this module is to convert the speech
wave form to some type of parametric representation at a
considerably rate. The heart of any speaker recognition
features from the speech and face recognition. They are
basically categorized into level of speech and level of
authentication. The version of Text and face recognition is
going to be help of the security purpose. The Text
Modulation and verification is helps to the banking sector
and other sectors to be used in future. Modulation of Text
and Recognition of face is the high level security of the
Smart Authentication System.
10. REFERENCES:
1) McCallum and W. Li, “Early results for named entity
recognition with conditional random fields, feature
induction and web-enhancedlexicons,“inProceedings
of the Seventh Conference on Natural Language
Learning at HLT-NAACL 2003 - Volume 4, ser. CONLL
’03, Stroudsburg, PA, USA, 2003, pp. 188–191.
2) Zhou and J. Su, “Named entity recognition using an
hmm-based chunk tagger,” in Proceedings of the 40th
Annual Meeting on Association for Computational
Linguistics, ser. ACL ’02, Stroudsburg, PA, USA,
2002,pp. 473–480.
3) D. M. Blei, A. Y. Ng, and M. I. Jordan, “Latent dirichlet
allocation,” J Mach. Learn. Res., vol. 3, pp. 993–1022,
2003.
4) M.Rosen-Zvi, T. Griths, M. Steyvers, and P. Smyth, “The
author-topic model for authors and documents,” in
Proceedings of the 20th Conference on Uncertainty in
Artificial Intelligence, ser. UAI ’04, Arlington, Virginia,
United States, 2004, pp. 487–494.
5) R. Mihalcea and A. Csomai,“Wikify!linkingdocuments
to encyclopedic knowledge,” in Proceedings of the
sixteenth ACM conference on Conference on
information and knowledge management, ser. CIKM
’07, New York, NY, USA, 2007, pp. 233–242.
6) D. Milne and I. H. Witten, “Learning to link with
wikipedia,” in Proceedingsof the17thACMconference
on Information and knowledge management, ser.
CIKM ’08, New York, NY, USA, 2008, pp. 509–518.
7) S. Kulkarni, A. Singh, G. Ramakrishnan, and S.
Chakrabarti, “Collective annotation of wikipedia
entities in web text,” in Proceedings of the 15th ACM
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4792
SIGKDD international conference on Knowledge
discovery and data mining,ser.KDD’09,NewYork,NY,
USA, 2009, pp. 457–466.
8) X. Han and J. Zhao, “Named entity disambiguation by
leveraging Wikipedia semantic knowledge,” in
Proceedings of the 18th ACM conference on
Information and knowledge management, ser. CIKM
’09, NewYork, NY, USA, 2009, pp. 215–224.
9) “Structural semantic relatedness: A knowledge-based
method to named entity disambiguation,” in
Proceedings of the 48th Annual Meeting of the
Association forComputational Linguistics,ser.ACL’10,
Stroudsburg, PA, USA, 2010, pp. 50–59.
10) X. Han, L. Sun, and J. Zhao, “Collective entity linking in
web text: A graph-based method,” in Proceedings of
the 34th International ACM SIGIR Conference on
Research and Development in Information Retrieval,
ser. SIGIR ’11, New York, NY, USA, 2011, pp. 765–774.

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IRJET- Voice Modulation and Verification for Smart Authentication System

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4787 VOICE MODULATION AND VERIFICATION FOR SMART AUTHENTICATION SYSTEM S. VISHNUPRIYA1, J. SUJATHA2 1PG Scholar, Department of MCA, Arulmigu Meenakshi Amman College of Engineering, Anna University, Vadamavandal (near Kanchipuram), India. 2Assistant professor, Department of MCA, Arulmigu Meenakshi Amman College of Engineering, Anna University, Vadamavandal (near Kanchipuram), India. ----------------------------------------------------------------------***--------------------------------------------------------------------- ABSTRACT:- Biometric is physical characteristic unique to each individual. It has a very useful application in authentication and access control. The designed system is a text-prompted version of voice biometric which incorporates text-independent speaker verification and speaker-independent speech verificationsystemimplementedindependently.Thefoundationforthis joint system is that the speech signal conveys boththespeechcontentandspeakeridentity.Suchsystemsare more-securefrom playback attack, since the word to speak during authentication is not previously set. During the course of the project various digital signal processing and pattern classification algorithms were studied. Short time spectral analysis was performed to obtain MFCC, energy and their deltas as feature. Feature extraction module is same for both systems. Speaker modelling was done by GMM and Left to Right Discrete HMM with VQ was used for isolated word modelling. And resultsofbothsystemswere combined to authenticate the user. The speech model for each word was pre-trained by using utterance of 45 English words. The speaker model was trained by utterance of about 2 minutes each by 15 speakers. While uttering the individual words,the recognition rate of the speech recognition system is 92 % and speaker recognition system is 66%. For longer duration of utterance (>5sec) the recognition rate of speaker recognition system improves to 78%. 1. INTRODUCTION A Text involvesTraditional andScientific Methods to improve the quality of the Text to voice recognition. Scientific methods of Text training need to be introduced for further improvement with our present day empirical methodology. The process of enriching the Text is known as Text culture. It involves training the Text to sing or speak in a particular desired way. It is a procedure where one learns to master one‘s Text. This study includes traditional and scientific methods to improvethequalityof Text. Fundamentally Text culture refers to the methodology adapted to train or control the Text to sing effectively. The dynamism, perfect control and freedom of the Text and the uplifting and inspiring effect of the performance. The entire vocalizing mechanism involves coordinated action of various muscles initiated by the brain combined with a sense of purpose to express a thought or idea.―Text culture is the coming together of an understanding of science (to a high degree) with the physical feel of the Text. We will have to understand the terms anchoring, focusing, erection and fusion of the Text itself. 2. SYSTEM ANALYSES 2.1 Existing System Currently the viable authentication mechanisms is use are password or PIN based. A user wishers to beauthenticated enters a short string or a number which is supposedlyeasy to remember, but is easy to forget and the authenticating machine checks the hash of the password against a stored hash in a database. If a user were to forget his or her password or it was stolen by someone wishing to steal the user’s identities of the user becomes endangered and easy to compromise. A common solution to the problem is to implement a biometric authentication mechanism such as retina scans or fingerprint based authentication. The advantage of this a retina or a fingerprint cannot be forgotten and it is unique to each user. Whilesucha system us extremely difficult to compromise, the cost of implementation restricts its development. In addition, if such biometric data was in fact compromised, the result would be disastrous for the user- he or she cannot change fingerprints or retinas. 2.2 Proposed System: The system proposed to solve both theproblemof password based authentication and biometric authentication is via Text Verification Using Back Propagation. The hardware necessary for Text verification is inexpensive and it can be deployed in (E.g. credit card machines in stores, tablet PCs, ATM machine).The system is proposed to overcome authenticating problem in Text verification withthehelp of Back propagation Algorithm. Any person in this world can never sign a same Text every time in their life time. His/her Text will be differing from time to time. When the user is in a calm mood the Text will be very different than the Text of the same user in a hurry or in a bad mood. So to overcome this problem Back propagation Algorithm this is one of the best neural network techniques to train the artificial neuron to recognize the different type of Text of same user. If the neurons are fine-tuned they can provide us the best authentication security.
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4788 3. SOFTWARE REQUIREMENT SPECIFICATIONS 3.1 Introduction to .NET Framework  The Microsoft .NET Framework is a software technology that is available with several software windows operating systems.  It includes a large library ofpre-codedsolutionsto common programming problems and a virtual machine that manages the execution of the programs written specifically for the framework.  The pre-coded solutions that form the framework’s Base Class Library cover a large range of programming needs ina numberofareas, including user, interface, data access, database connectivity, cryptography, web application development, numeric algorithms and network communications.  The class library is used by programmers, who combine if with their own code to produce applications.  Programmers written for the .NET framework executes in the software environment that manages the program’s runtime requirements. Also part of the .NET framework, this runtime environment is known as the common Language Runtime (CLR). 4. SYSTEM IMPLEMENTATION: 4.1 USER DETAILS MANAGEMENT: In this module user details along with user original Text is stored in the database. The Text will beconvertedinto binary format & stored as OLE objectindatabase.Initiallythe variance for comparison is set to an acceptable value. All the database operations are doneinSQL usingstoredprocedures concept. 4.2 TEXT CAPTURING: 4.4 TEXT RETIEVAL FROM DATABASE 4.4.1 LEARNING TEXT In this module a new Text is got from user as input, after that Text is processed as follows. The number of Text strokes, timing of strokes, Text proportions and stroke length. If any of the process results in variance less than the initial variance, then absolute difference are calculated between the new variance and initial variance. If the error or difference is not minimized to a value, the average is taken between new and initial variance. This average is taken as a input variance for another new Text. Again the difference is calculated if the error is not minimized the above process is repeated until error is minimized. The application user must stop only if he is satisfied with the result. If the error is minimized final variance and last error is stored in database, for next phase of verifying Text. 4.4.2 TEXT PROPORTION VERIFICATION The Text proportion we use both the height and width will be checked. For finding the height and width of the Text it use the Get Bounding Box () method. This method return the height and width value of the Text. This method returns the height and width of every node in the Text. Using the height and width oftheTexttheverification is done separately for height of the Text and the width of the Text separately. 4.4.3 TEXT PROPRTION IN WIDTH The width of the both the Text is found using the GetBoundingBox() method and by combining the width of two Text the output variance will be calculated and this output variance is compared with the input variance and if the output variance is greater than input variance then the Text is rejected. 4.4.4 TEXT PROPRTION IN HEIGHT The Height of the both the Text is found using the GetBoundingBox() method and by combining the width of two Text the output variance will be calculated and this output variance is compared with the input variance and if the output variance is greater than input variance then the Text is rejected.
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4789 4.5 Modulation Techniques The Communications Toolbox™ supports modulation these techniques for digital data. All the methods at the far right are implemented in library blocks. Like analog modulation, digital modulation alters a transmittable signal according to the information in a message signal. However, for digital modulation the message signal is restricted to a finite set. Modulation functions output the complex envelope of the modulated signal. Using the Communications Toolbox, you can modulate or demodulate signals using various digital modulation techniques, and plot signal constellations. 5. UML DIAGRAM UML standsforUnifiedModelingLanguage.UMLis a standardized general-purpose modeling language in the field of object-orientedsoftwareengineering.Thestandard is managed, and was created by, the Object Management Group. The goal is for UML to become a common language for creating models of object oriented computer software. In its current form UML is comprised of two major components: A Meta-model and a notation. In the future, some form of method or process may also be added to or associated with UML. The Unified Modeling Language is a standard language for specifying, Visualization, Constructing and documenting the artifacts of software system, as well as for business modeling and other non- software systems. The UML represents a collection of best engineering practices that have proven successful in the modeling of large and complex systems. The UML is a very important part ofdeveloping objectsorientedsoftwareand the software development process. The UML uses mostly graphical notations to express the design of software projects. 5.1 ER DIAGRAM: 5.2 CLASS DIAGRAM: In software engineering, a class diagram in the Unified Modeling Language (UML) is a type of static structure diagram that describes the structure of a system by showing the system's classes, their attributes, operations (or methods), and the relationships among the classes. It explains which class contains information. 5.3 SEQUENCE DIAGRAM: A sequence diagram in Unified Modeling Language (UML) is a kind of interaction diagram that shows how processes operate with one another and in what order. It is a construct of a Message Sequence Chart. Sequence diagrams are sometimes called event diagrams, event scenarios, and timing diagrams.
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4790 6. SYSTEM TESTING Testing virtual to the success of the system. System testing makes logical assumption that if all the parts system are correct, the goal will be successfully achieved. This system is tested by following test cases and prepared for final implementation. 6.1 TYPES OF TESTING 6.2.1 UNIT TESTING Unit testing involves the design of test cases that validate that the internal program logic is functioning properly, and that program input produces valid outputs. All decision branches and internal code flow should be validated. It is the testing of individual softwareunitsofthe application. It is done after the completion of an individual unit before integration. This is a structural testing, that relies on knowledge of its constructionandisinvasive.Unit tests perform basic tests at component level and test a specific business process, application, and/or system configuration. Unit tests ensure that each unique path of a business process performs accurately to the documented specifications and contains clearly defined inputs and expected results. 6.2.2 INTEGRATION TESTING Integration tests are designed to test integrated software components to determine if they actually run as one program. Integration tests demonstrate that although the components were individually satisfaction, as shown by successfully unit testing, the combination of components is correct andconsistent.Integrationtestingis specifically aimed at exposing the problemsthatarisefrom the combination of components. 6.2.3 FUNCTIONAL TESTING Functional tests provide systematic demonstrations that functions tested are available as specified by the business and technical requirements, system documentation and user manuals. 6.2.4 SYSTEM TESTING System testing ensures that the entire integrated software system meets requirements. It tests a configuration to ensure known and predictable results.An example of system testing is the configuration oriented system integration test. System testing is based on process descriptions and flows, emphasizing pre-driven process links and integration points. 6.2.5 WHITE BOX TESTING White Box Testing is a testing in which in which the software tester has knowledge of the inner workings, structure and language of the software, or at least its purpose. It is purpose. It is used to test areasthatcannot be reached from a black box level. 6.2.6 BLACK BOX TESTING Black Box Testing is testing the software without any knowledge of the inner workings, structure or language of the module being tested. Black box tests, as most other kinds of tests, must be written from a definitive source document, such as specification or requirements document, such as specification or requirements document. It is a testing in which the software undertestis treated, as a black box .you cannot “see” into it. The test provides inputs and responds to outputs without considering how the software works. 6.2.7 ACCEPTANCE TESTING User Acceptance Testing is a critical phase of any project and requires significant participation by the end user. It also ensures that the system meets the functional requirements. Functional testing is centered on the following items: Valid Input : identifiedclassesofvalid input must be accepted. Invalid Input : identified classes of invalid input must be rejected. Functions : identifiedfunctionsmust be exercised. Output : identified classes of application outputs must be exercised. Systems/Procedures.
  • 5. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4791 7. OTHER TESTING METHODOLOGIES 7.1 User Acceptance Testing User Acceptance of a system is the key factor for the success of any system. The system underconsideration is tested for user acceptancebyconstantlykeepingintouch with the prospective system users at the time of developing and making changes wherever required. The system developed provides a friendly user interface that can easily be understood even by a person who is new to the system. 7.2 Output Testing After performing the validation testing, the next step is output testing of the proposed system, since no system could be useful if it does not produce the required output in the specified format. Asking the users about the format required by them tests the outputs generated or displayed by the system under consideration. Hence the output format is considered in 2 ways – one is on screen and another in printed format. 7.3 Validation Checking Validation checks are performed on the following fields. 7.4 Text Field: The text field can contain only the number of characters lesser than or equal to its size. The text fields are alphanumeric in some tables and alphabetic in other tables. Incorrect entry always flashes and error message. 7.5 Numeric Field: The numeric field can contain only numbersfrom 0 to 9. An entry of any character flashes an error messages. The individual modules are checked for accuracyandwhat it has to perform. Each module is subjected to test run along with sample data. The individually tested modules are integrated into a single system. Testing involves executing the real data information is used in the program the existence of any program defect is inferred from the output. The testing should be planned so that all the requirements are individually tested. A successful test is one that gives out the defects for the inappropriate data and produces and output revealing the errors in the system interfacing systems or procedures must be invoked. 8. CONCLUSION In this project, I have presented an exercise survey of smart authentication system, I have categorized the modules in speaker recognition and discussed different approaches for each module. In addition to this, I have presented study of the various typical searchbeingcarried out in the field of speaker recognition. I have also discussed issued and challenges pertaining to the speaker recognition system and face recognition system for smart authentication systems.And alsoIdidsmartauthentication for large sectors for security purpose. This project is used for security or Network Security by the coming generation to used this security system. 9. FUTURE ENHANCEMENT The purpose of this module is to convert the speech wave form to some type of parametric representation at a considerably rate. The heart of any speaker recognition features from the speech and face recognition. They are basically categorized into level of speech and level of authentication. The version of Text and face recognition is going to be help of the security purpose. The Text Modulation and verification is helps to the banking sector and other sectors to be used in future. Modulation of Text and Recognition of face is the high level security of the Smart Authentication System. 10. REFERENCES: 1) McCallum and W. Li, “Early results for named entity recognition with conditional random fields, feature induction and web-enhancedlexicons,“inProceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003 - Volume 4, ser. CONLL ’03, Stroudsburg, PA, USA, 2003, pp. 188–191. 2) Zhou and J. Su, “Named entity recognition using an hmm-based chunk tagger,” in Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, ser. ACL ’02, Stroudsburg, PA, USA, 2002,pp. 473–480. 3) D. M. Blei, A. Y. Ng, and M. I. Jordan, “Latent dirichlet allocation,” J Mach. Learn. Res., vol. 3, pp. 993–1022, 2003. 4) M.Rosen-Zvi, T. Griths, M. Steyvers, and P. Smyth, “The author-topic model for authors and documents,” in Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence, ser. UAI ’04, Arlington, Virginia, United States, 2004, pp. 487–494. 5) R. Mihalcea and A. Csomai,“Wikify!linkingdocuments to encyclopedic knowledge,” in Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, ser. CIKM ’07, New York, NY, USA, 2007, pp. 233–242. 6) D. Milne and I. H. Witten, “Learning to link with wikipedia,” in Proceedingsof the17thACMconference on Information and knowledge management, ser. CIKM ’08, New York, NY, USA, 2008, pp. 509–518. 7) S. Kulkarni, A. Singh, G. Ramakrishnan, and S. Chakrabarti, “Collective annotation of wikipedia entities in web text,” in Proceedings of the 15th ACM
  • 6. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4792 SIGKDD international conference on Knowledge discovery and data mining,ser.KDD’09,NewYork,NY, USA, 2009, pp. 457–466. 8) X. Han and J. Zhao, “Named entity disambiguation by leveraging Wikipedia semantic knowledge,” in Proceedings of the 18th ACM conference on Information and knowledge management, ser. CIKM ’09, NewYork, NY, USA, 2009, pp. 215–224. 9) “Structural semantic relatedness: A knowledge-based method to named entity disambiguation,” in Proceedings of the 48th Annual Meeting of the Association forComputational Linguistics,ser.ACL’10, Stroudsburg, PA, USA, 2010, pp. 50–59. 10) X. Han, L. Sun, and J. Zhao, “Collective entity linking in web text: A graph-based method,” in Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, ser. SIGIR ’11, New York, NY, USA, 2011, pp. 765–774.