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ASRoIL: a comprehensive survey for automatic speech recognition of Indian languages

  • Amitoj Singh
  • Virender Kadyan
  • Munish KumarEmail author
  • Nancy Bassan
Article
  • 19 Downloads

Abstract

India is the land of language diversity with 22 major languages having more than 720 dialects, written in 13 different scripts. Out of 22, Hindi, Bengali, Punjabi is ranked 3rd, 7th and 10th most spoken languages around the globe. Expect Hindi, where one can find some significant research going on, other two major languages and other Indian languages have not fully developed Automatic Speech Recognition systems. The main aim of this paper is to provide a systematic survey of the existing literature related to automatic speech recognition (i.e. speech to text) for Indian languages. The survey analyses the possible opportunities, challenges, techniques, methods and to locate, appraise and synthesize the evidence from studies to provide empirical answers to the scientific questions. The survey was conducted based on the relevant research articles published from 2000 to 2018. The purpose of this systematic survey is to sum up the best available research on automatic speech recognition of Indian languages that is done by synthesizing the results of several studies.

Keywords

Automatic speech recognition Indian languages Feature extraction techniques Classification techniques Speech corpus 

Notes

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Amitoj Singh
    • 1
  • Virender Kadyan
    • 2
  • Munish Kumar
    • 1
    Email author
  • Nancy Bassan
    • 3
  1. 1.Department of Computational SciencesMaharaja Ranjit Singh Punjab Technical UniversityBathindaIndia
  2. 2.Department of Computer Science and Engineering, Chitkara University Institute of Engineering and TechnologyChitkara UniversityRajpuraIndia
  3. 3.Department of Mechanical EngineeringBaba Farid College of Engineering and TechnologyBathindaIndia

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