We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

A Survey on Isolated Word and Digit Recognition using Different Techniques

by Pooja Prajapati, Miral Patel
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 161 - Number 3
Year of Publication: 2017
Authors: Pooja Prajapati, Miral Patel
10.5120/ijca2017913130

Pooja Prajapati, Miral Patel . A Survey on Isolated Word and Digit Recognition using Different Techniques. International Journal of Computer Applications. 161, 3 ( Mar 2017), 6-15. DOI=10.5120/ijca2017913130

@article{ 10.5120/ijca2017913130,
author = { Pooja Prajapati, Miral Patel },
title = { A Survey on Isolated Word and Digit Recognition using Different Techniques },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2017 },
volume = { 161 },
number = { 3 },
month = { Mar },
year = { 2017 },
issn = { 0975-8887 },
pages = { 6-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume161/number3/27126-2017913130/ },
doi = { 10.5120/ijca2017913130 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:06:43.970552+05:30
%A Pooja Prajapati
%A Miral Patel
%T A Survey on Isolated Word and Digit Recognition using Different Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 161
%N 3
%P 6-15
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nowadays, Spoken digit recognition is one the challenging task in the field of speech recognition. Spoken digit recognition is necessary nowadays in many applications that needed number as input like telephone dialing using speech, addresses, airline reservation & automatic directory to retrieve & send information which make the system more efficient to use. Also, It proves very helpful for physically challenged people in hands & eyes free applications. Various techniques are used for isolated speech recognition like MFCC, HMM, LPC. But among all of them many researchers found that MFCC is widely used & give a more accurate result. ASR achieves a maturity level in many Indian languages. Mostly research work has been carried out. Here in this paper, Discussions of the survey is on some of that recent research work in isolated digit recognition for the Indian languages like English, Gujarati, and Hindi & also in other similar languages. Likewise, discussing different approaches, methods & comparative analysis about recent research work done in isolated digit & word recognition in various languages.

References
  1. Choudhary Annu, Chauhan R, S, Gupta Gautam, “Automatic Speech Recognition System for Isolated & Connected Words of Hindi Language By Using Hidden Markov Model Toolkit (HTK)”, Association of Computer Electronics and Electrical Engineers, (ACEEE) 2013
  2. Singhal Shweta, Dubey Rajesh Kumar, “Automatic Speech Recognition For Connected Words Using DTW/HMM For English /Hindi Languages ”, IEEE 2015
  3. H. B. Chauhan, Prof. B. A. Tanawala , “Comparative Study Of MFCC & LPC Algorithms For Gujarati Isolated Word Recognition ” , IJIRCCE , FEB-2015, VOL.3, ISSUE 2
  4. Pandit Purnima, Bhatt Shardav, “Automatic Speech Recognition Of Gujarati Digits Using Dynamic Time Warping ” , IJEIT , June-2014, VOL.3, ISSUE 12
  5. Chapaneri , Santosh V, Jayaswal, Deepak J, “Efficient Speech Recognition System For Isolated Digits”, IJCSET, 2013, VOL.4, ISSUE 3, pp (228-236)
  6. Patel Bharat C, Desai Apurva A, “Recognition of Spoken Gujarati Numeral and Its Conversion into Electronic Form ” , IJERT, 2014, VOL.3, ISSUE 9
  7. Safäa ELOUAHABI, Mohamed ATOUNTI, Mohamed BELLOUKI, “Amazigh Isolated Word Speech Recognition System Using Hidden Markov Model Toolkit (HTK) ” , IEEE, 2016
  8. Therese S Shanthi, Lingam Chelpa , “Speaker Based Language Independent Isolated Speech Recognition System” , IEEE, 2015
  9. Mishra A N, Biswas Astik, Chandra, Mahesh, “Isolated Hindi Digit Recognition: A Comparative Study, International Journal of Electronics and Communication Engineering (IJECE)”, Jan-2010, VOL.3, ISSUE 1, pp (229-238)
  10. MarutiLimkara, RamaRaob & Vidya Sagvekarc, “Isolated Digit Recognition Using MFCC & DTW”, IJAEEE, 2012 , VOL.1, ISSUE 1 , pp (59-64)
  11. Revathi A, Venkataramani Y, “ Speaker Independent Continuous Speech & Isolated Digit Recognition Using VQ & Hmm ” , IEEE , 2011, pp(198-202)
  12. Patil Mahesh K, Admuthe, Prof L S , Zirmite, Prashant P , “Isolated Digit Recognition Using Ear Microphone Data Using MFCC, VQ & HMM” , IJETT, ,Jun-2014 , VOL.12, ISSUE 7 , pp (322-325)
  13. Vaibhavi Trivedi , “A Survey On English Digit Speech Recognition Using HMM ” ,VOL.2, ISSUE 3, IJSER , 2013, pp (247-253)
  14. Saksamudre, Suman K, “Comparative Study Of Isolated Word Recognition System For Hindi Language” , IJERT, JUL-2015, VOL.4, ISSUE 7 ,pp (536-540)
  15. Nandyala, Siva Prasad , “ Real Time Isolated Word Speech Recognition System For Human Computer Interaction” International Journal of Computer Applications , NOV-2010, VOL.12, ISSUE 2
  16. Mengdi Yuet, Ling Chen, Jie Zhang, Hong Liu , “Speaker Age Recognition Based On Isolated Words By Using SVM” , IEEE, 2014, pp(282-286)
  17. Londhe, Narendra D , “Hybrid HMM/ANN Based Isolated Hindi Word Recognition”, IEEE,2014 , ISSUE1
  18. Tailor, Jinal H, Shah, Dipti B, “Review On Speech Recognition System For Indian Language” , IJCA, Jun-2015, VOL.119, ISSUE 2, pp (975-8887)
  19. Dhandhania Vedanta, Hansen Jens Kofod, Kandi , Shefali Jayanth, Ramesh, Arvind, “Robust Speaker Independent Speech Recognizer For Isolated Hindi Digits ” , IJCCE, Nov-2012, VOL.1, ISSUE 4, pp (483-485)
  20. Abushariah, Ahmad A M, Gunawan Teddy S, Khalifa, Othman, Abushariah, Mohammad A M , “ English Digit Speech Recognition System Based On HMM ” , IEEE , May-2010, pp (11-13)
  21. K . H .Davis, R Biddulph & S balashek, “ Automatic Speech Recognition of Spoken Digits”, J.A.S.A, 1952 ,VOL.24, ISSUE 6 , pp (637-642)
  22. L R Rabiner ,A E Rosenberg & S E Levinson , “ Considerations In Dynamic Time Warping Also For Discrete Word Recognition” , IEEE , Dec -1978, Vol.1
  23. T Pruthi , S Saksena & P K Das, “Isolated Word Recognition For Hindi Language Using VQ & Hmm ” , IIT-Madras , ICMPS
  24. M Dua R K Agrgarwal, V Kadayan & S.Dua , “ Punjabi Automatic Speech Recognition Using HTK” , IJCSI, Jul-2012, Vol.9
  25. L R RABINAR, M R Sambur, “ Voiced –Unvoiced Silence Detection Using LPC Distance Measure ” VOL.2 , pp(323-326) , IEEE international conference on ICASSP
  26. M A Bush , G E Kopec & N Lauritzen, “ Segmentation In Isolated Word Recognition Using VQ” VOL-9, IEEE, 1984 , international conference on ICASSP.
  27. S C Sajjan & C. Vijaya , “Comparison Of DTW & HMM For Isolated Word Recognition”, IEEE, 2012, PP (466-470)
  28. R Kumar , “Comparison Of HMM & DTW For Isolated Word Recognition System For Punjabi Language” , IJSC ,2010, Vol.5, Pp(88-92)
  29. Ramona Rao ,G.V & Srichand J ,“Word Boundary Detection Using Pitch variations ”, pp(813-816), International Conference On Spoken Language ICSLP , May-1996
  30. I Bhardwaj & N D Londhe, “Hidden Markov Model Based Isolated Hindi Word Recogntion ” IEEE, 2012,
  31. A.Sharma & A Kaur , “ Automatic Segmentation Of Punjabi Speech Into Syllable Like Units Using Group Delay A Review ” , IJCSET , Jun-2013, VOL.4, pp (2229-3345)
  32. G Kaur ,P Singh & A Kaur , “ Syllable Boundary Detection System For Punjabi Language”, Vol.1, IJARC July-2013
  33. L R Rainer & M.R.Sambur, “AN Algorithm For Determining The Endpoints Of Isolated Utterances” , 1975,pp(297-315), The Bell System Technical Journal
  34. Gattal, Abdeljalil , Chibani, Youcef , Jedi, Chawki, Siddiqi, Imran , “Improving Isolated Digit Recognition Using a Combination of Multiple Features” , IEEE, 2014
  35. Ms. Rupali S Chavan , “An Implementation of Text Dependent Speaker Independent Isolated Word Speech” , IJESRT, 2013,VOL.2, ISSUE 9
  36. Sabah, Reem, Ainon Raja N , “Isolated digit speech recognition in Malay language using neuro-fuzzy approach” , IEEE , 2009 , pp(336-340)
  37. Mustafa, Akram A , “Performance Evaluation of Artificial Neural Networks for Isolated Hindi Digit Recognition with LPC and MFCC” , IEEE 2015,vol.4, issue 4
  38. Mishra A N,Biswas, Astik, Chandra Mahesh, “Isolated Hindi Digits Recognition: A Comparative Study” , IJECE, 2010,Vol.3,Issue 1
  39. Ms.Puspa Machhar, Mr.Dipak Agrawal , “HMM Based Gujarati Tricky Words Recognition” , IJARIIE, 2016, Vol.2 ,Issue 3
  40. Bhoomika Dave, D. S. Pipalia, “An Approach To Increase Word Recognition Accuracy In Gujarati Language”, International Journal Of Innovative Research In Computer And Communication Engineering, 2015, Vol.3, Issue 10
  41. J Baheti, M,V Kale K,E Jadhav M, “Comparison Of Classifiers For Gujarati Numeral Recognition”, 2011, Vol.3, Issue 3, international Journal Of Machine Intelligence
  42. M.A.Anusuya, S.K.Katti , “Speech Recognition By Machine: A Review” , Ijcsis 2009 , Vol. 6, No. 3
  43. Shall Gujral , Monika Tuteja , Baljit Kaur , ”Various Issues In Computerized Speech Recognition Systems ” ,International Journal Of Engineering Research And General Science , June-July 2014, Volume 2, Issue 4
  44. Santosh K.Gaikwad, Bharti W.Gawali , Pravin Yannawar , “A Review On Speech Recognition Technique ”International Journal Of Computer Applications, November 2010, Volume 10
  45. Suma Swamy1 And K.V Ramakrishnan , “An Efficient Speech Recognition System” , Computer Science & Engineering: An International Journal (CSEIJ) , August 2013, Vol. 3, No. 4
  46. Neha Chadha, R.C. Gangwar, Rajeev Bedi , “Current Challenges and Application of Speech Recognition Process using Natural Language Processing: A Survey” , IJCA, Dec-2015 ,vol.131
  47. Ika Novita Dewi, Fahri Firdausillah, Catur Supriyanto , “Sphinx-4 Indonesian Isolated Digit Speech Recognition”, Journal Of Theoretical And Applied Information Technology (JATIT) , July-2013, Vol.53
  48. Sumit Kumar Ghanty , Soharab Hossain Shaikh, Nabendu Chaki, “On Recognition Of Spoken Bengali Numerals” , IEEE, 2010
  49. Suman K. Saksamudre, P.P. Shrishrimal R.R. Deshmukh , “ A Review On Different Approaches For Speech Recognition System” , IJCA , Apr-2015, Vol.115
  50. Karpagavalli, S, Rani, K Usha Deepika, R,Kokila, P , “Isolated Tamil Digits Speech Recognition using Vector Quantization” , International Journal of Engineering Research & Technology (IJERT), 2012, VOL.1, ISSUE 4, pp(1-12)
  51. Darabkh, Khalid A Khalifeh, Ala F Bathech, Baraa A , Sabah, Saed W, “Efficient DTW-Based Speech Recognition System for Isolated Words of Arabic Language” ,International Journal of Computer, Electrical, Automation, Control and Information Engineering , 2013, VOL.7 , ISSUE 5, pp(586-593)
  52. Bishnu Prasad Das1, Ranjan Parekh , “Recognition of Isolated Words uses Features based on the LPC, MFCC, ZCR and STE, with Neural Network Classifiers” , International Journal of Modern Engineering Research (IJMER) , May-June 2012, , Vol.2, Issue.3, pp (854-858)
Index Terms

Computer Science
Information Sciences

Keywords

Speech Recognition MFCC Hidden Markov Model (HMM) LPC Isolated word isolated digit recognition.