Survey On Speech Recognition Using Hidden MARKOV Model

Authors

  • Pradhan A Department of Computer Science & Engineering, Girijananda Chowdhury Institute of Management and Technology (GIMT), Guwahati, India
  • Paul N Department of Computer Science & Engineering, Girijananda Chowdhury Institute of Management and Technology (GIMT), Guwahati, India
  • Das K Department of Computer Science & Engineering, Girijananda Chowdhury Institute of Management and Technology (GIMT), Guwahati, India
  • Bordoloi RJ Department of Computer Science & Engineering, Girijananda Chowdhury Institute of Management and Technology (GIMT), Guwahati, India
  • Baruah D Department of Computer Science & Engineering, Girijananda Chowdhury Institute of Management and Technology (GIMT), Guwahati, India

Keywords:

MARKOV Model, HMM

Abstract

Modeling a signal model for recognizing speech is a tough job. Here we will find out how Hidden Markov Model (HMM) is used in modeling speech recognition application. The steps: Preprocessing, Feature Extraction and Recognition and Hidden Markov Model which used in recognition phase, are used to design a complete Automatic Speech Recognition System (ASR). Researchers are trying to model a perfect ASR system but computer machines are not able to match up to our expectations due to lack of accuracy of matching and inefficient speed of response. In speech recognition three different approaches which are broadly used are Acoustic phonetic approach, knowledge based approach and Pattern recognition approach. This study is based on pattern recognition approach using Hidden Markov Model which is studied in detail as HMMs are found to yield best performance among all the available techniques.

References

. D.B. Paul,.Speech Recognition Using Hidden Markov Models,The Lincoln Laboratory Journal, Volume 3, Number 1,1990

. Nirav S. Uchat,Hidden Markov Model and Speech Recognition,Department of Computer Science and Engineering Indian Institute of Technology, Bombay Mumbai

. Bhupinder Singh, NehaKapur, Puneet Kaur,Speech Recognition with Hidden Markov Model: A Review ,International Journal of Advanced Research in Computer Science and Software Engineering, IGCE Abhipur, Mohali (Pb.), India, Volume 2, Issue 3, March 2012

. Mikael Nilsson Marcus Ejnarsson,Speech Recognition using Hidden Markov Model performance evaluation in noisy environment,Department of Telecommunications and Signal Processing Blekinge Institute of Technology March, 2002

. Balwant A.Sonkamble and Dr. D. D. Doye,Hidden Markov Model for Speech Recognition

. Using Modified Forward-Backward Re-estimation Algorithm ,IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 2, July 2012 ISSN (Online): 1694-0814

. Mr. Sanjay Bhardwaj, Mr. Sunil Pathania, Mr. Rajesh Akela,Speech Recognition using Hidden Markov Model and Viterbi Algorithm ,International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE) Volume 4, Issue 5, May 2015

. Waleed Abdulla, Nikola Kasabov,The Concepts of Hidden Markov Model in Speech Recognition,The Information Science Discussion Paper Series Number 99/09 May 1999 ISSN 1177-455X

. Ms. Rupali S Chavan1, Dr. Ganesh. S Sable2, “An Overview of Speech Recognition Using HMM, An Overview of Speech Recognition Using HMM, International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology, IJCSMC, Vol. 2, Issue. 6, June 2013, pg.233 – 238

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Published

2025-11-11

How to Cite

[1]
A. Pradhan, N. Paul, K. Das, R. J. Bordoloi, and D. Baruah, “Survey On Speech Recognition Using Hidden MARKOV Model”, Int. J. Comp. Sci. Eng., vol. 4, no. 7, pp. 158–161, Nov. 2025.

Issue

Vol. 4 No. 7 (2016): IJCSE Special Issue December Edition

Section

Survey Article

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