Speech Recognition Using MATLAB and Cross-Correlation Technique

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  •   Ledisi Giok Kabari

  •   Marcus B. Chigoziri

Abstract

Speech is a prominent communication method among humans, whereas the communication between human and computers were based on text user interface and graphic user interface. Speech recognition is used in almost every security project where you need to speak and tell your password to computer and is also used for automation. This paper demonstrates a model that enhances technological advancement where humans and computers interact via voice user interface. In developing the model, cross correlation was implemented in MATLAB to compare two or more signals and detect the most accurate one of the all. We are actually used cross correlation to find similarity between our recorded Signal files and the testing signal. Thus we were able to develop a model where machines can differentiate between commands and act upon them.


Keywords: Cross Correlation, MATLAB, Recorded Signal, Signal Processing, Speech Recognition, Testing Signal

References

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M. Saundade and P. Kurle, “Speech Recognition using Digital Signal Processing”, International Journal of Electronics, Communication & Soft Computing Science and Engineering ISSN: 2277-9477, Volume 2, Issue 6, 2013.

S. Karpagavalli and E. Chandra, “Review on Automatic Speech Recognition Architecture and Approaches”, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9, No.4, (2016), pp.393 -404, http://dx.doi.org/10.14257/ijsip.2016.9.4.34.

A. Gupta1, P. Raibagkar, A. Palsokar, “Speech Recognition Using Correlation Technique”, International Journal of Current Trends in Engineering & Research (IJCTER)e-ISSN 2455–1392 Volume 3 Issue 6, June 2017 pp. 82 –89.

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How to Cite
[1]
Kabari, L. and Chigoziri, M. 2019. Speech Recognition Using MATLAB and Cross-Correlation Technique. European Journal of Engineering Research and Science. 4, 8 (Aug. 2019), 1-3. DOI:https://doi.org/10.24018/ejers.2019.4.8.1437.