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Spoken Language Identification for Native Indian Languages Using Deep Learning Techniques

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Machine Learning and Autonomous Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 269))

Abstract

In this paper, we present a Spoken Language Identification System (LID) for native Indian languages. LID task aims to determine the spoken language in a speech utterance of an individual. In this system, ‘Resemblyzer’ is used for feature extraction, which derives a high-level representation of a voice in the form of a summary vector of 256 values. Experimentation is done on ‘IndicTTS Database’, developed by IIT Madras which comprises 13 languages, and ‘Open-source Multi-speaker Speech Corpora’ database developed by the European Language Resources Association which consists of 7 languages. The work consists of training Deep Neural Networks (DNN), Recurrent Neural Networks with Long Short-Term Memory (RNN–LSTM) and Gaussian Mixture Model (GMM) on each database for 1.5 and 5 s feature lengths and comparing their performances with each other and in each scenario.

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Authors and Affiliations

  1. Department of Electronics Engineering, Vishwakarma Institute of Technology, Pune, India

    Rushikesh Kulkarni

  2. Department of Electronics and Telecommunication Engineering, Vishwakarma Institute of Technology, Pune, India

    Aditi Joshi & Milind Kamble

  3. Anubhooti Solutions, Pune, India

    Shaila Apte

Authors
  1. Rushikesh Kulkarni
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  2. Aditi Joshi
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  3. Milind Kamble
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  4. Shaila Apte
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Corresponding author

Correspondence to Aditi Joshi .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Dayeh University, Changhua, Taiwan

    Joy Iong-Zong Chen

  2. Go Perception Laboratory, Cornell University, Ithaca, NY, USA

    Haoxiang Wang

  3. Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada

    Ke-Lin Du

  4. Department of Information Science and Engineering, Dayananda Sagar College of Engineering, Bangalore, India

    V. Suma

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Kulkarni, R., Joshi, A., Kamble, M., Apte, S. (2022). Spoken Language Identification for Native Indian Languages Using Deep Learning Techniques. In: Chen, J.IZ., Wang, H., Du, KL., Suma, V. (eds) Machine Learning and Autonomous Systems. Smart Innovation, Systems and Technologies, vol 269. Springer, Singapore. https://doi.org/10.1007/978-981-16-7996-4_7

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