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HMM-Based Lightweight Speech Recognition System for Gujarati Language

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Information and Communication Technology for Sustainable Development

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 10))

Abstract

Speech recognition system (SRS) is growing research interest in the area of natural language processing (NLP). To develop speech recognition system for low resource language is difficult task. This paper defines a lightweight speech recognition system approach for Indian Gujarati language using hidden Markov model (HMM). The aim of this research is to design and implement SRS for routine Gujarati language which is difficult due to language barrier, complex language framework, and morphological variance. To train the HMM-based SRS we have manually created speech corpora that contained 650 routine Gujarati utterances which are recorded from total 40 speakers of South Gujarat region. Total numbers of speakers are selected on the basis of gender. We have achieved accuracy of 87.23% with average error rate 12.7% based on the word error rate (WER) computing.

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Author information

Authors and Affiliations

  1. S.P. University, Vallabh Vidhyanagar, Gujarat, India

    Jinal H. Tailor

  2. G.H. Patel Post Graduate Department of Computer Science, S.P. University, Vallabh Vidhyanagar, Gujarat, India

    Dipti B. Shah

Authors
  1. Jinal H. Tailor
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  2. Dipti B. Shah
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Correspondence to Jinal H. Tailor .

Editor information

Editors and Affiliations

  1. Microsoft Innovation Centre, Sri Aurobindo Institute of Technology, Indore, Madhya Pradesh, India

    Durgesh Kumar Mishra

  2. Dagenham, United Kingdom

    Malaya Kumar Nayak

  3. Department of Information Technology, Sabar Institute of Technology, Ahmedabad, Gujarat, India

    Amit Joshi

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Tailor, J.H., Shah, D.B. (2018). HMM-Based Lightweight Speech Recognition System for Gujarati Language. In: Mishra, D., Nayak, M., Joshi, A. (eds) Information and Communication Technology for Sustainable Development. Lecture Notes in Networks and Systems, vol 10. Springer, Singapore. https://doi.org/10.1007/978-981-10-3920-1_46

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  • DOI: https://doi.org/10.1007/978-981-10-3920-1_46

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3919-5

  • Online ISBN: 978-981-10-3920-1

  • eBook Packages: EngineeringEngineering (R0)

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