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By,
Rajaganapathy S
VIT UNIVERSITY
conversion of Sign Language to
speech using Kinect
Aim and Objective:
• The aim of the project is to build a tool for the people
who is unable to hear or speak. It should be modest,
easy to use and recognize a users gestures with a
highest degree of accuracy, so that users do not have
to repeat themselves often, which can be annoying.
• The system should run on readily available
commercial platforms, and must be cost effective. So
that the poor background people may also use the app
effectively.
Introduction
• Sign language is a system of communication using
visual gestures and signs, as used Hearing impaired
people.
• But none of the sign languages are universal or
international. A person should know the sign
language to understand the language;
• This becomes complicated when a person who has
inability to speak or hear wants to convey something
to a person or group of persons, since most of them
are not familiar with the sign language.
Techniques
● Locate specific joint from all 20 joints
● Gather X,Y, Z coordinates
● Compare coordinates with predefined dataset values
Detailed Design:
Module Description
• human gestures input stream
Kinect Receiving Gestures
Application Match Gestures
Convert Text into Speech
Results:
Conclusion:
• The project is aimed to minimize the major
complexity in the system for further extensions, the
sensor comes with the feature of face recognition and
voice recognition and therefore the next phase of the
project would be adding face recognition for
capturing the expressions which in turn increases the
productivity of the application by adding a little more
accuracy
References
• [1] Jungong Han, Enhanced Computer Vision with
Microsoft Kinect Sensor, A
• Review, IEEE TRANSACTIONS ON CYBERNETICS.
• [2] Microsoft Kinect SDK,http://www.microsoft.com/en-
us/kinectforwindows/.
• [3] ] Gunasekaran. K, Manikandan. R, International
Journal of Engineering and
• Technology (IJET): Sign Language to Speech
Translation System Using PIC
• Microcontroller.
• [4] RiniAkmeliawatil, Melanie PO-LeenOoi et al,Real-
Time Malaysian Sign.

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Conversion of sign language to speech using kinect

  • 1. By, Rajaganapathy S VIT UNIVERSITY conversion of Sign Language to speech using Kinect
  • 2. Aim and Objective: • The aim of the project is to build a tool for the people who is unable to hear or speak. It should be modest, easy to use and recognize a users gestures with a highest degree of accuracy, so that users do not have to repeat themselves often, which can be annoying. • The system should run on readily available commercial platforms, and must be cost effective. So that the poor background people may also use the app effectively.
  • 3. Introduction • Sign language is a system of communication using visual gestures and signs, as used Hearing impaired people. • But none of the sign languages are universal or international. A person should know the sign language to understand the language; • This becomes complicated when a person who has inability to speak or hear wants to convey something to a person or group of persons, since most of them are not familiar with the sign language.
  • 4. Techniques ● Locate specific joint from all 20 joints ● Gather X,Y, Z coordinates ● Compare coordinates with predefined dataset values
  • 6. Module Description • human gestures input stream
  • 11. Conclusion: • The project is aimed to minimize the major complexity in the system for further extensions, the sensor comes with the feature of face recognition and voice recognition and therefore the next phase of the project would be adding face recognition for capturing the expressions which in turn increases the productivity of the application by adding a little more accuracy
  • 12. References • [1] Jungong Han, Enhanced Computer Vision with Microsoft Kinect Sensor, A • Review, IEEE TRANSACTIONS ON CYBERNETICS. • [2] Microsoft Kinect SDK,http://www.microsoft.com/en- us/kinectforwindows/. • [3] ] Gunasekaran. K, Manikandan. R, International Journal of Engineering and • Technology (IJET): Sign Language to Speech Translation System Using PIC • Microcontroller. • [4] RiniAkmeliawatil, Melanie PO-LeenOoi et al,Real- Time Malaysian Sign.