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Reseach Article

Current Challenges and Application of Speech Recognition Process using Natural Language Processing: A Survey

by Neha Chadha, R.C. Gangwar, Rajeev Bedi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 131 - Number 11
Year of Publication: 2015
Authors: Neha Chadha, R.C. Gangwar, Rajeev Bedi
10.5120/ijca2015907471

Neha Chadha, R.C. Gangwar, Rajeev Bedi . Current Challenges and Application of Speech Recognition Process using Natural Language Processing: A Survey. International Journal of Computer Applications. 131, 11 ( December 2015), 28-31. DOI=10.5120/ijca2015907471

@article{ 10.5120/ijca2015907471,
author = { Neha Chadha, R.C. Gangwar, Rajeev Bedi },
title = { Current Challenges and Application of Speech Recognition Process using Natural Language Processing: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 131 },
number = { 11 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 28-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume131/number11/23495-2015907471/ },
doi = { 10.5120/ijca2015907471 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:27:03.853699+05:30
%A Neha Chadha
%A R.C. Gangwar
%A Rajeev Bedi
%T Current Challenges and Application of Speech Recognition Process using Natural Language Processing: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 11
%P 28-31
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Speech recognition is a vast research field for researchers in modern era. Earlier, the human language was processed by the computer system for speech recognition. Thus, the main objective is to develop recognition system which improves human to human communication by enabling human-machine communication by processing of text or speech. Various applications of speech recognition systems are present and these all includes various research challenges. A critical machine learning based review is defined which addresses the various challenging tasks of speech recognition system in NLP. In the existing systems, the recognition rate is very less and the noise ration during the recognition process creates a problem. Thus in this literature review we try to address such kind of challenges and provides a solution to work further in future.

References
  1. Anupam Choudhary, Ravi Kshirsagar, 2012 Process Speech Recognition System using Artificial Intelligence Technique In International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-2, Issue-5.
  2. Alexandre Trilla, 2012 Natural Language Processing in Text to Speech synthesis and Automatic Speech Recognition In IEEE, VOL.4
  3. Daniel Jurafsky, James H. Martin, 2000 Speech and Language Processing In Pearson Education, pp-1-975.
  4. D D Doye, T R Sontakke & Smita Nagtode, 2015 The Nonlinear Time Alignment Model for Speech In IETE Journal of Research, Taylor & Francis, pp 1-6.
  5. Dr. Kavitha, Nachammai, Ranjani, Shifali., 2014 Speech Based Voice Recognition System for Natural Language Processing In International Journal of Computer Science and Information Technologies, Vol. 5
  6. Elyes Zarrouk, Yassine Ben Ayed, Faiez Gargouri, 2014 Hybrid continuous speech recognition systems by HMM, MLP and SVM: a comparative study, International Journal of Speech Technology ,Volume 17, Issue 3, pp 223-233.
  7. Fook, C.Y. ; Sch. of Mechatron. Eng., Univ. Malaysia Perlis , Arau, Malaysia ; Hariharan, M. ; Yaacob, S. ; Adom, A., 2012 A review: Malay speech recognition and audio visual speech recognition In Biomedical Engineering (ICoBE), International Conference.
  8. Jayashree Padmanabhan and Melvin Jose Johnson Prem kumar, 2015 Machine Learning in Automatic Speech Recognition: A Survey, IETE Technical Review, Taylor & Francis, pp-1-13.
  9. Kenji Sagae and Gwen Christian and David DeVault and David R. Traum, 2009 Towards Natural Language Understanding of Partial Speech Recognition Results in Dialogue System In Proceedings of NAACL HLT 2009: Short Papers, pages 53–56, Boulder, Colorado M.A. Anusuya , S.K.Katti 2009 Speech Recognition by Machine: A Review In international Journal of Computer Science and Information Security, Vol. 6, No. 3.
  10. Mohammad , Alessandro Gasparetto, 2014 A system for feature classification of emotions based on Speech Analysis; Applications to Human-Robot Interaction In Proceeding of the 2nd RSI/ISM International Conference on Robotics and Mechatronics , Tehran, Iran.
  11. Poonam.S.Shetake, S.A.Patil, P. M Jadhav, 2014 Review of text to speech conversion methods, international Journal of Industrial Electronics and Electrical Engineering, Volume-2, Issue-8, pp-29-35.
  12. Qirong Mao, Ming Dong, Zhengwei Huang, and Yongzhao ZhanLearning, 2014 Salient Features for Speech Emotion Recognition Using Convolutional Neural Networks, In IEEE transactions on multimedia, vol. 16, no. 8.
  13. Siva Prasad Nandyala and T. Kishore Kumar,2014 Hybrid HMM/DTW based Speech Recognition with Kernel Adaptive Filtering Method In International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.1, Suma Swamy and K.V Ramakrishnan 2013 An efficient speech recognition system, Computer Science & Engineering: An International Journal (CSEIJ), Vol. 3, No. 4.
  14. Xiang-Lilan, Zhang, Zhi-Gang, Luo,Ming Li, 2014 Merge-Weighted Dynamic Time Warping for Speech Recognition In Journal of Computer Science and Technology ,Volume 29, Issue 6, pp 1072-1082.
  15. Zue V, Glass, J., Goodine, D., Leung, H., Phillips, M, Polifroni, J., Seneff, S,2011 Integration of speech recognition and natural language processing in the mit voyager system, IEEE.
Index Terms

Computer Science
Information Sciences

Keywords

NLP GUI MFCC LFCC LPC KLM LIF HMM DTW SAE.