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Group members Luke Makischuk Abderahmane Sebaa Ameneh Sadat Yazdaninik Asma Faizi Professor: R Habash TA: Wei Yang - PowerPoint PPT Presentation


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Group members Luke Makischuk Abderahmane Sebaa Ameneh Sadat Yazdaninik Asma Faizi Professor: R Habash TA: Wei Yang Introduction The purpose of our project was to implement an efficient voice recognition algorithm and improve upon the idea’s from the IEEE paper:

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Slide1 l.jpg

Group members

Luke Makischuk

Abderahmane Sebaa

Ameneh Sadat Yazdaninik

Asma Faizi

Professor: R Habash

TA: Wei Yang


Introduction l.jpg
Introduction

  • The purpose of our project was to implement an efficient voice recognition algorithm and improve upon the idea’s from the IEEE paper:

    “Speech Recognition and Its Application in Voice-based Robot Control System” by Luo Zhizeng and Zhao Jinghing, August 2004

  • In the article, they used a technique called pattern-comparison to implement the voice recognition which 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.


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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 a 1000-word speech recognition system” Kavaler, R.A.; Lowy, M.; Murveit, H.; Brodersen, R.W, Volume 22,  Issue 1,  Feb 1987

  • “Significance of the Modified Group Delay Feature in Speech Recognition” Rajesh M. Hegde; Hema A. Murthy; Venkata Ramana Rao Gadde; Volume 15,  Issue 1,  Jan. 2007

  • Lawrence Rabiner, Biing-Hwangluang, Fundomenrols Of Speech Recognition, Qinghua Press, 1999

  • http://cslu.cse.ogi.edu/HLTsurvey/ch1node7.html


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Work distribution

  • Asma and Ameneh -Voice recognition research/algorithm and report writeup

  • Abderahmane and Luke-Matlab coding


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Voice recognition

  • All done using Matlab

    Recognized voice commands:

  • Stop

  • Turn Left

  • Turn Right

  • Move Forward

  • Move Backwards

  • Only works with one person’s voice but can easily be trained to work with anyone's voice


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Voice recognition

How it works

  • Record voice command (Time domain)

  • Transform into frequency domain using Fourier Transform and get the magnitude spectrum

  • Compare spectrum of voice commands



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Fourier transform

Speech Signal (time domain) Frequency domain


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Communication with a robot

  • The efficient way to communicate with robot is using Bluetooth.

  • We connect the Bluetooth to the serial port at the back of the PC to transmit to the robot.

  • For receiving, we connect a receiver module to the robot.


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Continue

  • The robot receives the input commands from the Bluetooth transmitter which is a 3 bit digital signal. Then, if the input commands are matched to the program, the robot moves based on state given. Otherwise, the robot will not respond to the given command.


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Continue

  • The programmed commands:




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Results

94 % accurate


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Limitations

  • The amount of words that could be recognized by our program was limited, the more words we tried adding, the less accurate it became

  • The voice recognition program only works for the person’s voice who is trained for it

  • Program is less accurate in noisy environments

  • Bluetooth is an expensive technology to implement


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Advantages

  • Simple algorithm used for voice recognition

  • Easy to train a person’s voice

  • Accurate

  • Bluetooth is very fast and efficient

  • Voice commands are a very easy way to control a robot


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Conclusion

  • For small vocabulary applications, the method of using the Fourier transform based speech recognition is more suitable then the other complex algorithms for it is easy to implement and has a high accuracy rate.


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Thank you for your time

any Questions?


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