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Linear Discriminant Analysis Based Approach for Automatic Speech Recognition of Urdu Isolated Words

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Book cover Communication Technologies, Information Security and Sustainable Development (IMTIC 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 414))

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Abstract

Urdu is amongst the five largest languages of the world and enjoys extreme importance by sharing its vocabulary with several other languages of the Indo-Pak. However, there has not been any significant research in the area of Automatic Speech Recognition of Urdu. This paper presents the statistical based classification technique to achieve the task of Automatic Speech Recognition of isolated words in Urdu. For each isolated word, 52 Mel Frequency Cepstral Coefficients have been extracted and based upon these coefficients; the classification has been achieved using Linear Discriminant Analysis. As a prototype, the system has been trained with audio samples of seven speakers including male/female, native/non-native and speakers with different ages while the testing has been done using audio samples of three speakers. It was determined that majority of words exhibit a percentage error of less than 33 %. Words with 100 % error were declared to be bad words. The work reported in this paper may serve as a strong baseline for future research work on Urdu ASR, especially for continuous speech recognition of Urdu.

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Acknowledgment

The authors are thankful to the supporting staff of the Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan. It is due to their efforts which they put into keeping the Computer Lab open for extra hours and providing the authors with opportunity to use it. The authors also extend their gratitude to Engr. Salman Ilahi, Department of Electrical Engineering and Engr. Irfan Ahmad, Department of Industrial Engineering, UET Peshawar, for their valuable input and suggestions throughout this work.

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Authors and Affiliations

  1. Department of Communication Engineering, School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 10083, China

    Hazrat Ali & Xianwei Zhou

  2. Department of Computer Systems Engineering, University of Engineering and Technology Peshawar, Peshawar, 25120, Pakistan

    Nasir Ahmad

  3. Department of Electrical and Computer Engineering, North Dakota State University, Fargo, ND, 58108-6050, USA

    Muhammad Ali

  4. Department of Computer Systems Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan

    Ali Asghar Manjotho

  5. Machine Learning Group, School of Informatics, City University London, London, EC1V 0HB, UK

    Hazrat Ali

Authors
  1. Hazrat Ali
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  2. Nasir Ahmad
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  3. Xianwei Zhou
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  4. Muhammad Ali
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  5. Ali Asghar Manjotho
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Corresponding author

Correspondence to Hazrat Ali .

Editor information

Editors and Affiliations

  1. University of Umm Al-Qura, Makkah, Saudi Arabia, Mehran University of Engineering and Technology, Jamshoro, Pakistan

    Faisal Karim Shaikh

  2. Faculty of Electrical, Electronics and Computer Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan

    Bhawani Shankar Chowdhry

  3. College of Communication and Information, University of Kentucky, Lexington, Kentucky, USA

    Sherali Zeadally

  4. Department of Energy Technology, Aalborg University, Esbjerg, Denmark

    Dil Muhammad Akbar Hussain

  5. Department of Telecommunication Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan

    Aftab Ahmed Memon

  6. Department of Electrical Engineering, Mehran University of Engineering and Technology, Jamshoro, Pakistan

    Muhammad Aslam Uqaili

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Ali, H., Ahmad, N., Zhou, X., Ali, M., Manjotho, A.A. (2014). Linear Discriminant Analysis Based Approach for Automatic Speech Recognition of Urdu Isolated Words. In: Shaikh, F., Chowdhry, B., Zeadally, S., Hussain, D., Memon, A., Uqaili, M. (eds) Communication Technologies, Information Security and Sustainable Development. IMTIC 2013. Communications in Computer and Information Science, vol 414. Springer, Cham. https://doi.org/10.1007/978-3-319-10987-9_3

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  • DOI: https://doi.org/10.1007/978-3-319-10987-9_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10986-2

  • Online ISBN: 978-3-319-10987-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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