Five Stage Dynamic Time Warping Algorithm for Speaker Dependent Isolated Word Recognition in Speech

Authors

  • Yadav M Dept. of IT , Guru Tegh Bahadur Institute of Technology, New Delhi.
  • Aalam A Dept. of CS, Jamia Hamdard, Hamdard Nagar New Delhi,

Keywords:

Dynamic time warping, speech recognition, speaker dependent

Abstract

In speech recognition, a speaker dependent isolated word recognition system is used for small vocabulary in different applications for voice control systems. Dynamic Time Warping (DTW) algorithm is used for pattern matching when two sequences of unequal size are available. When test data and reference data or sequences are available of unequal in nature with time domain then existing DTW algorithm takes time more, while proposed solution will give the efficient algorithm which reduces the computation time without degradation of accuracy and efficiency.

References

Titus Felix FURTUNA, Dynamic Programming Algorithms in Speech Recognition, Revista Informatica Economica nr. 2(46), 2008, pp 94- 99.

B. H. Jaung and L.R. Rabiner , Automatic Speech Recognition – A Brief History of The Technology, Elsevier Encyclopedia of Language and Linguistics, Second Edition, 2005.

Rubita Sudirman, Sh.-hussain Salleh, Ting Chee Ming, Local DTW Coefficients and pitch feature for back-propagation NN digit recognition. Proceedings of the IASTED International Conference on Networks and Communication Systems 2006. pp-201-206.

Ghazi Al- Naymat, Sanjay Chawala, Javid Taheri, Sparse DTW A Novel Approach to Speed up Dynamic Time Warping, Proc. of 8th Australasian Data Mining Conference (AusDM’09), pp 117- 127.

Tiberius Zaharia, Svetlana Segarceanu, Marius Cotescu, Alexandru Spataru, “ Quantized Dynamic Time Warping (DTW) Algorithm” , IEEE, 2010, pp 91-94.

L.R. Rabiner and R. W. Schafer, Thery and Applications of Digital Speech Processing, Prentice Hall Inc., 2011.

L.R. Rabiner and R. W. Schafer, Introduction to Digital Speech Processing, Foundations and Trends in Signal Processing, Vol. 1, Nos. 1-2, NOW Publishers, Boston, pp. 1-200, 2007.

S. Dusan and L.R. Rabiner. Can Automatic Speech Recognition Learn More From Human Speech Perception, Trens in Speech Technology, Proc. of the third conference on Speech Technology and Human Computer Dialogue. pp. 21-36, May 2005.

Eiji Mizutani, The Dynamic Time Warping Algorithms. Lecture Note for Mechanical Engineering Seminar, Tokyo Metropolitan University. 2006. pp 1-11.

Rubita Sudirman, Sh.-hussain Salleh. Ting Chee Ming, NN Speech Recognition Utilizing Aligned DTW Local Distance Scores, ICMT-192. pp 1-5.

Sakoe, H. & S. Chiba.(1978) Dynamic programming algorithm optimization for spoken word recognition. IEEE, Trans. Acoustics, Speech and Signal Proc., Vol. ASSP-26. pp 43-49.

Somya Adwan, Hamzah Arof, A Novel Double Stage Dynamic Time Warping Algorithm for Image Template Matching, Proceeding of the 6th IMT-GT Conference on Mathematics, Statistics and its Applications (ICMSA 2010), University Tunku Abdul Rahman , Kaula Lumpur Malaysia. Pp. 667-676.

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Published

2025-11-11

How to Cite

[1]
M. Yadav and A. Aalam, “Five Stage Dynamic Time Warping Algorithm for Speaker Dependent Isolated Word Recognition in Speech”, Int. J. Comp. Sci. Eng., vol. 4, no. 10, pp. 112–115, Nov. 2025.