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Advances in Data and Information Sciences pp 425–432Cite as

A Time Delay Neural Network Acoustic Modeling for Hindi Speech Recognition

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 94))

Abstract

Automatic Speech Recognition (ASR) systems have become more popular recently for low resource languages. India has 22 official language and more than two thousands other regional languages, the majority have low resources. The standard resources are also limited for the Hindi language. In this paper, the implementation of continuous Hindi ASR system has been done using Time Delay Neural Network (TDNN) based acoustic modeling significantly improves the performance of baseline Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) based Hindi ASR system up to 11%. Further improvement of 3% and 2% have been recorded by applying i-vector adaptation, interpolated language modeling in this work.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, National Institute of Technology, Kurukshetra, Haryana, India

    Ankit Kumar & R. K. Aggarwal

  2. Computer Science and Engineering Department, Galgotias University, Greater Noida, India

    Ankit Kumar

Authors
  1. Ankit Kumar
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  2. R. K. Aggarwal
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Corresponding author

Correspondence to Ankit Kumar .

Editor information

Editors and Affiliations

  1. Smart Grid and Renewable Energy, University of Agder, Kristiansand, Norway

    Mohan L. Kolhe

  2. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Shailesh Tiwari

  3. Department of Computer Science and Engineering, NIT Agartala, Tripura, India

    Munesh C. Trivedi

  4. Computer Science and Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India

    Krishn K. Mishra

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Kumar, A., Aggarwal, R.K. (2020). A Time Delay Neural Network Acoustic Modeling for Hindi Speech Recognition. In: Kolhe, M., Tiwari, S., Trivedi, M., Mishra, K. (eds) Advances in Data and Information Sciences. Lecture Notes in Networks and Systems, vol 94. Springer, Singapore. https://doi.org/10.1007/978-981-15-0694-9_40

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  • DOI: https://doi.org/10.1007/978-981-15-0694-9_40

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0693-2

  • Online ISBN: 978-981-15-0694-9

  • eBook Packages: EngineeringEngineering (R0)

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