presentation voice recognition

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HARDENING VOICE BASED AUTHENTICATION SYSTEMS BY ENHANCING CONFIDENTIALITY AND INTEGRITY FOR SECURE ENTRY POINTS Objective to Improve Integrity and Confidentiality using Matlab Programming by HARDEER KAUR UNIVERSITY ROLL NO. 1/11/FET/COM/3003 MASTER OF TECHNOLOGY IN COMMUNICATION SYSTEM Session 2011 to 2014

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Page 1: Presentation voice recognition

HARDENING VOICE BASED AUTHENTICATION SYSTEMS BY ENHANCING CONFIDENTIALITY AND INTEGRITY FOR SECURE

ENTRY POINTS

Objective to Improve Integrity and Confidentiality using Matlab Programming

byHARDEER KAUR

 

UNIVERSITY ROLL NO. 1/11/FET/COM/3003 MASTER OF TECHNOLOGY IN

 COMMUNICATION SYSTEM Session 2011 to 2014

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• Knowledge-based authentication is based on information authorized individuals will know, and unauthorized individuals will not. E.g. a PIN or password information.

• Object-based authentication is based on possessing a token or tools that perm it’s the person access to the controlled resource. E.g. Keys, pass cards or a secure Id.

• Biometric-based authentication measures individual’s unique physical or behavioral characteristics. It exists today in various form s such as fingerprint verification, retinal scans, facial analysis, analysis of vein structures and voice authentication.

SECURITY SYSTEMS & AUTHENTICATION.

Authentication:

Authentication techniques have been developed to stop the unauthorized access to a data or any object for that mater. who can access our resources is controlled using three main methods:

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Authentication:

Various Authentication techniques have been developed to ease the authorized and stop the unauthorized access to system.

Basic evolution of authentication can be summarized as follows. • Password: This can be considered as the most basic and

effective level of security, where in a user define unique password is assigned to a particular resource. If someone wants to access the resource he needs to enter the defined password.

• Software Tokens: This is similar to have software generated password. Where a software token is generated by a separate system which can be entered as a password to gain an access to another system.

• Digital certificate: Is an electronic document that uses a digital signature to bind a public key with an identity information such as the name of a person or an organization, their address, and so forth.

• Hardware Tokens: Is a physical device that an authorized user of computer services is given to ease authentication

• Smart Cards:  is any pocket-sized card with embedded integrated circuits. 

• Biometrics: A system for controlling access to storage units based on physical details, such as fingerprints.

DEVELOPMENT OF AUTHENTICATION SYSTEM

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This can be achieved in two ways as described below.

1. Voice to text approach (Speech recognition) : Voice signals can be converted to text and further this text can be given as a password to an existing security system. This will help in increasing the access tote data. Example: A Voice enabled ATM for disabled (Blind) users: Imagine an ATM machine to whom you can talk to, it can answer all your queries and can help you to access to your account.

2. Biometric approach (Speaker recognition) : Every human being has his own unique voice and this can be used as an digital signature to authenticate his access to various systems. Example: A voice enabled net banking website, which will ask it’s users to read a phrase every time he wants to login. The phrase will be scrutinized on the bases of it’s tone, pitch and other parameters to identify the user.

3. Combination of Voice to text and Biometric approach: In this approach the system will check for the integrity to the speaker and also will check the content of the speech.Example: At the security gate the user will be asked to enter his password (which can be a sequence of alphabets or phrase).

USE OF VOICE AS AN INPUT TO THE SECURITY SYSTEM

Voice can be used as an input signal which can be used to authenticate an access to a system or resource.

Voice command can be used as an input to almost all the security systems thereby increasing the level of security and improve the ease of access.

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USE OF VOICE AS AN INPUT TO THE SECURITY SYSTEM

Comparison between the three approaches of voice based security systems.

Voice to text approach (Speech recognition)

Biometric approach (Speaker recognition)

Combination of Voice to text and

Biometric approach

Used to synthesize “What user is trying to say”.

Used to identify “Who is speaking”.

Used to identify the Speaker as well as the content.

Applications:

1. Voice based command systems that can be used to control of operations of various equipments.

2. Interactive voice response systems used at telephone based enquiry terminals.

Applications:

1. Voice based user authentication systems.

Applications:

1. Voice based user authentication systems.

2. Real time language translation with speaker tagging.

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VOICE RECOGNITION

Introduction: Voice or Speech recognition is terminology give to the study of the voice and convert it to digital

signal which can be used as a command or trigger for some other operation.

Goal: To automatically extract the string of words spoken from the speech signal.

SpeechRecognition

Words“How are you?”

Speech Signal

Speech is produced as sequence of characters, which has characteristics of Acoustic Signal

Input Speech

AcousticFront-end

AcousticFront-end

Acoustic ModelsP(A/W)

Acoustic ModelsP(A/W)

RecognizedUtterance

SearchSearchLanguage

Model P(W)

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Milestone in speech recognition.

Since 1930, a simple speech machine that responds to a limited small set of words was invented. This machine was able to respond to spoken utterances and produce the speech. Since then, it has driven many-researched interest to invent a speech recognition system.

Following are some major milestones in the history of speech processing.

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Approach

Speech Recognition Approaches

Automatic speech recognition system is used to transform or produce a sequence of message from a speech signal. This process is called decoding. Speech signal is decoded and then converted into writing (e.g. dictation machine) or commands to be processed (e.g. hands free dialing).  Speech recognition systems can be divided into the number of classes based on their ability to recognize that words and list of words they have. A few classes of speech recognition are classified as under: 1. Isolated Speech: Isolated words usually involve a pause

between two utterances; it doesn’t mean that it only accepts a single word but instead it requires one utterance at a time.

2. Connected Speech: Connected words or connected speech is similar to isolated speech but allow separate utterances with minimal pause between them.

3. Continuous speech: Continuous speech allow the user to speak almost naturally, it is also called the computer dictation Continuous speech:

“This is a very good presentation”

Connected speech: “This” , “presentation”

Isolated speech: “T” , “h” , “I”, “s”

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COMPONENTS OF SPEECH RECOGNITION SYSTEM

SpeechRecognition

Words“How are you?”

Speech Signal

Speech Signals : Input signals (Voice) is collected using a Microphone (Transducer) and are converted form sound wave to electric signal.

Parameterization: The signal received is converted to a Digital signal for further processing.

Acoustic Modeling: Acoustic models represent sub-word units, such as phonemes, as a finite-state machine in which:

• states model spectral structure and• transitions model temporal structure.

Most commonly used modeling approaches followed are:• Hidden Markov Models• Parameter Estimation.

Language Modeling : The language model predicts the next set of words, and controls which models are hypothesized.Most commonly used modeling approaches followed are:

• N-Grams Models• Integration of natural language Model.

Search Algorithms and Data Structures

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PARAMETERIZATION

Steps Procedure Description

1Sample the analog signal regularly.

The sampling rate must be twice the highest frequency to produce playback that appears neither choppy nor too smooth

2 Quantize the sample.

Quantization consists of a scale made up of eight major divisions or chords. Each chord is subdivided into 16 equally spaced steps. The chords are not equally spaced but are actually finest near the origin. Steps are equal within the chords but different when they are compared between the chords. Finer graduations at the origin result in less distortion for low-level tones.

3Encode the value into

digital form.

PBX output is a continuous analog voice waveform. T1 digital voice is a snapshot of the wave encoded in ones and zeros.

The human voice produces a highly complex acoustic wave, which, fortunately, the human ear and brain have evolved to interpret effectively. In technical terms the voice is an analog signal. An analog signal is defined as one with a continuously variable physical value. A single frequency tone, such as the dial tone on a telephone will be a simple analog signal. Such a simple signal will take the form of a Sine WaveIn explaining how analog signals can be converted to digital data, as shown in the figure.

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SCOPE OF PROJECT WORK

Objective of this project:

To study the behavior of the sound wave and use it’s characteristics to develop a voice based security system.

Develop a Matlab programs to simulate a security gate where voice string is used as a password (Text to speech).

Further Study:

Develop a Matlab program to simulate a security gate where identity of the speaker is used as a password (Speaker Identification).

Develop a Matlab program to simulate a security gate where identity of the speaker and voice string is used as a password (Biometric authentication & Voice passwords).

In order to satisfy the goal of the research following objectives have been identified:

1. Study the Speech Processing techniques.

2. Study the Speech processing research methods.

3. Use and test various speech recognition models.

4. Selection and Creation of an improved speech recognition technique.

5. Test and compare the results with existing systems.

6. Test in the real-time on local and online voice print data.

Tools To Be Used.

7. Matlab.8. Microsoft word.

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ADVANTAGES & DIADVANTAGES

ADVANTAGES OF THE SOFTWARE. 1. Provide additional security gate if the software is used along with the existing security

systems.

2. Provide significant help for the people with disabilities.

3. Able to write the text through both keyboard and voice input.

4. Voice recognition of different notepad commands such as open save and clear.

5. Open different windows software, based on voice input.

6. Requires less consumption of time in writing text.

7. Lower operational costs.   DISADVANTAGES 8. Low accuracy

9. Not good in the noisy environment

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CONCLUSION

The main purpose and benefit of a voice recognition system is the amount of security that it provides. Although voice recognition is mostly secure, it still has flaws. To aid its acceptance, this biometric system can be combined with more traditional security features to provide an additional layer of security. These can include using other biometrics, or security mechanisms such as RSA, PINs or a combination of several different mechanisms. Through further development, voice recognition can be one of the most successful and largest applications of biometrics in the future to come.

A crude speaker recognition code has been written using the MATLAB programming language Experience was also gained in speech editing as well as basic filtering techniques. While the methods utilized in the design of the code for this project are a good foundation for a speaker recognition system, more advanced techniques would have to be used to produce a successful speaker recognition system.

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REFRERANCES

1. A Practical guide to Biometric Security Technology, Silverm an, 2001, IEEE.

2. Digital Communication by, Haykin.

3. Digital Communication by, Sunjay Sharma.

4. Digital Signal Processing, J. S. Katre

5. Speech Technology for Telecommunications, F.A. Westhall, R.D. Johnston.

6. Voice Recognition, Jim Baumann, Human Interface Technology Laboratory, University of Washington. http://www.hitl.washington.edu/scivw/EVE/I .D.2.d.VoiceRecognition.htm l

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THANK YOU &

Q & A