Automatic Speech Recognition: A Review

  ijett-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2013 by IJETT Journal
Volume-4 Issue-2                       
Year of Publication : 2013
Authors : Preeti Saini , Parneet Kaur


Preeti Saini , Parneet Kaur. "Automatic Speech Recognition: A Review". International Journal of Engineering Trends and Technology (IJETT). V4(2):132-136 Feb 2013. ISSN:2231-5381. published by seventh sense research group


After years of research and development the accuracy of automatic speech recognition ( ASR ) remains one of the most important research challenges e.g. speaker and language variability, vocabulary size and domain, noise. The design of speech recognition syst em require careful attentions to the challenges or issue such as various types of speech classes, speech representation, feature extraction techniques, database and performance evaluation. This paper presents a study of basic approaches to speech recogniti on and their results shows better accuracy. This paper also presents what research has been done around for dealing with the problem of ASR.


[1] M.A.Anusuya and S.K.Katti , “ Speech Recognition by Machine: A Review ” , (IJCSIS) International Journal of Computer Science and Information Security, vol. 6, no. 3, pp. 181 - 205, 2009.
[2] Mohit Dua, R.K.Aggarwal, Virender Kadyan and Shelza Dua, “ Punjabi Automatic Speech Recognition Using HTK ” , IJCSI International Journal of Computer Science Issues, vol. 9, issue 4, no. 1, July 2012 .
[3] Rajesh Kumar Aggarwal and M. Dave, “ Acoustic modeling problem for automatic speech recognition system: advances and refinements Part (Part II) ” , Int J Speech Technol, pp. 309 – 320, 2011.
[4] Kuldeep Kumar, Ankita Jain and R.K. Aggarwal, “ A Hindi speech recognition system for connected words using HTK ” , Int. J. Computational Systems Engineering, vol. 1, no. 1, pp. 25 - 32, 2012.
[5] Kuldeep Kumar R. K. Aggarwal, “ Hindi speech recognition system using HTK ” , International Journal of Computing and Business Research, vol. 2, issue 2, May 2011.
[6] R.K. Aggarwal and M. Dave, “ Performance evaluation of sequentially combined heterogeneous feature streams for Hindi speech recognition system ” , 01 September 2011.
[7] Anusuya, M. A., & Katti, S. K.. Front end analysis of speech recognition: A review. International Journal of Speech Technology,Springer, v ol.14, pp. 99 – 145, 201 1.
[8] Jacob Benesty, M. Mohan Sondhi, and Yiteng Huang, Handbook of Speech Processing , Springer, 2008.
[9] Wiqas Ghai and Navdeep Singh,“ Literature Review on Automatic Speech Recognition”, International Journal of Computer Applications vol. 41 – no.8, pp. 42 - 50, March 2012.
[10] R K Aggarwal and M. Dave, “Markov Modeling in Hindi Speech Recognition System: A Review”, CSI Journal of Computing, v ol. 1, no.1,pp. 38 - 47, 2012.
[11] Dev, A. (2009) ‘Effect of retroflex sounds on the recognition of hindi voiced and unvoiced stops’, Journal of AI and Soc. , Springer, vol. 23, pp. 603 - 612

Automatic speech recognition, hidden markov model, acoustic model, MFCC